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#dbms search results

devwithjay's profile picture. Ui » Ux » Web Dev
Jay Kadlag
 @devwithjay
Apr 12

𝗙𝗿𝗼𝗺 𝗘𝗥𝗗 𝘁𝗼 𝗔𝗣𝗜 🏏 Designed a complete IPL management system from scratch today Started with ER diagram → entities, relations, junction tables Converted it into models and structured database properly Then moved to routes and actual backend flow #DBMS #ChaiCode

devwithjay's tweet image. 𝗙𝗿𝗼𝗺 𝗘𝗥𝗗 𝘁𝗼 𝗔𝗣𝗜 🏏 Designed a complete IPL management system from scratch today Started with ER diagram → entities, relations, junction tables Converted it into models and structured database properly Then moved to routes and actual backend flow #DBMS #ChaiCode
devwithjay's tweet image. 𝗙𝗿𝗼𝗺 𝗘𝗥𝗗 𝘁𝗼 𝗔𝗣𝗜 🏏 Designed a complete IPL management system from scratch today Started with ER diagram → entities, relations, junction tables Converted it into models and structured database properly Then moved to routes and actual backend flow #DBMS #ChaiCode
devwithjay's tweet image. 𝗙𝗿𝗼𝗺 𝗘𝗥𝗗 𝘁𝗼 𝗔𝗣𝗜 🏏 Designed a complete IPL management system from scratch today Started with ER diagram → entities, relations, junction tables Converted it into models and structured database properly Then moved to routes and actual backend flow #DBMS #ChaiCode
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BharukaShraddha's profile picture. AI Content Creator ⚡| Helping brands grow organically | Full-Stack Dev | Built AI tools& real-time apps🤝 🤝 | Collabs & freelance/remote roles → DM open 💌
Shraddha Bharuka
@BharukaShraddha
Aug 26

🚀 Database Management System (DBMS) is the backbone of every software system. I’ve made handwritten DBMS notes covering all key concepts. #SQL #Database #DBMS #HandwrittenNotes Sharing a few free pages here 🧵👇 1/n

BharukaShraddha's tweet image. 🚀 Database Management System (DBMS) is the backbone of every software system. I’ve made handwritten DBMS notes covering all key concepts. #SQL #Database #DBMS #HandwrittenNotes Sharing a few free pages here 🧵👇 1/n
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devwithjay's profile picture. Ui » Ux » Web Dev
Jay Kadlag
 @devwithjay
Apr 4

𝗗𝗮𝘁𝗮 𝘀𝗶𝗱𝗲 𝗯𝗲𝗴𝗶𝗻𝘀 📊 • Creating databases and tables • Inserting and selecting data • Filtering records • UPDATE table • DELETE with WHERE • ALTER TABLE operations • DISTINCT, sorting, LIMIT, OFFSET • Aggregations • GROUP BY #DBMS #SQL #Backend #ChaiCode

devwithjay's tweet image. 𝗗𝗮𝘁𝗮 𝘀𝗶𝗱𝗲 𝗯𝗲𝗴𝗶𝗻𝘀 📊 • Creating databases and tables • Inserting and selecting data • Filtering records • UPDATE table • DELETE with WHERE • ALTER TABLE operations • DISTINCT, sorting, LIMIT, OFFSET • Aggregations • GROUP BY #DBMS #SQL #Backend #ChaiCode
devwithjay's tweet image. 𝗗𝗮𝘁𝗮 𝘀𝗶𝗱𝗲 𝗯𝗲𝗴𝗶𝗻𝘀 📊 • Creating databases and tables • Inserting and selecting data • Filtering records • UPDATE table • DELETE with WHERE • ALTER TABLE operations • DISTINCT, sorting, LIMIT, OFFSET • Aggregations • GROUP BY #DBMS #SQL #Backend #ChaiCode
devwithjay's tweet image. 𝗗𝗮𝘁𝗮 𝘀𝗶𝗱𝗲 𝗯𝗲𝗴𝗶𝗻𝘀 📊 • Creating databases and tables • Inserting and selecting data • Filtering records • UPDATE table • DELETE with WHERE • ALTER TABLE operations • DISTINCT, sorting, LIMIT, OFFSET • Aggregations • GROUP BY #DBMS #SQL #Backend #ChaiCode
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rachit26227444's profile picture. CSE student | Learning Web Dev & Python Exploring AI/ML through projects Building in public
rachit
 @rachit26227444
Apr 12

Designed a complete IPL management system from scratch today Started with ER diagram → entities, relations, junction tables Converted it into models and structured database properly Then moved to routes and actual backend flow #DBMS #ChaiCode @nirudhuuu @ChaiCodeHQ

rachit26227444's tweet image. Designed a complete IPL management system from scratch today Started with ER diagram → entities, relations, junction tables Converted it into models and structured database properly Then moved to routes and actual backend flow #DBMS #ChaiCode @nirudhuuu @ChaiCodeHQ
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devwithjay's profile picture. Ui » Ux » Web Dev
Jay Kadlag
 @devwithjay
Apr 5

𝗝𝗼𝗶𝗻𝘀 & 𝗜𝗻𝗱𝗲𝘅𝗶𝗻𝗴 ⚡ Today’s class went deeper into SQL, joins, foreign keys, & constraints. Also explored indexing and how databases optimize queries behind the scenes. Designed an Instagram-like system using ER diagrams. #DBMS #SQL #Backend #ChaiCode

devwithjay's tweet image. 𝗝𝗼𝗶𝗻𝘀 & 𝗜𝗻𝗱𝗲𝘅𝗶𝗻𝗴 ⚡ Today’s class went deeper into SQL, joins, foreign keys, & constraints. Also explored indexing and how databases optimize queries behind the scenes. Designed an Instagram-like system using ER diagrams. #DBMS #SQL #Backend #ChaiCode
devwithjay's tweet image. 𝗝𝗼𝗶𝗻𝘀 & 𝗜𝗻𝗱𝗲𝘅𝗶𝗻𝗴 ⚡ Today’s class went deeper into SQL, joins, foreign keys, & constraints. Also explored indexing and how databases optimize queries behind the scenes. Designed an Instagram-like system using ER diagrams. #DBMS #SQL #Backend #ChaiCode
devwithjay's tweet image. 𝗝𝗼𝗶𝗻𝘀 & 𝗜𝗻𝗱𝗲𝘅𝗶𝗻𝗴 ⚡ Today’s class went deeper into SQL, joins, foreign keys, & constraints. Also explored indexing and how databases optimize queries behind the scenes. Designed an Instagram-like system using ER diagrams. #DBMS #SQL #Backend #ChaiCode
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tiwari_pee28336's profile picture. 💻 Web Development Learner ⚡ JavaScript | TypeScript | Backend 🚀 Building projects & sharing my dev journey in public 📈 Learning something new every day
Peeyush Tiwari
 @tiwari_pee28336
Apr 6

🚀 ER Diagram Assignment Done! Designed an Instagram-like thrift database — focused on structure, relationships & scalability. Grateful for the guidance 🙌 @Hiteshdotcom sir,@piyushgarg_dev @yntpdotme @nirudhuuu @surajtwt_ @devwithjay @ChaiCodeHQ #DBMS #SQL #LearningInPublic

tiwari_pee28336's tweet image. 🚀 ER Diagram Assignment Done! Designed an Instagram-like thrift database — focused on structure, relationships & scalability. Grateful for the guidance 🙌 @Hiteshdotcom sir,@piyushgarg_dev @yntpdotme @nirudhuuu @surajtwt_ @devwithjay @ChaiCodeHQ #DBMS #SQL #LearningInPublic
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kidehen's profile picture. Founder & CEO, OpenLink Software. 🔗 https://t.co/sTt5T5d1uA 🔗 https://t.co/VGVHGUGEHq 🔗 https://t.co/owcnsohhvA 🔗 https://t.co/FtJLPA3IDl
Kingsley Uyi Idehen
@kidehen
Feb 19, 2025

The importance of Data, Data Access, and Data Connectivity has never been more evident than in the age of AI. This makes data access protocols like ODBC even more critical, as they empower AI Agents and their underlying frameworks to remain Database Management System (#DBMS)

kidehen's tweet card. AI and the Need for Data Access and Connectivity Artificial Intelligence (AI) thrives on data. This makes data connectivity and structured retrieval crucial components of AI-driven applications,...
The Importance of ODBC and OpenLink ODBC Drivers in the Age of AI
Source: linkedin.com
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RajSing62691380's profile picture. Hey !
Raj Singh
 @RajSing62691380
Apr 9

Week 11 of my learning journey 🚀 Started **DBMS with Shubham Sir**. @Hiteshdotcom | @piyushgarg_dev |@nirudhuuu #DBMS #SQL #LearningJourney

RajSing62691380's tweet image. Week 11 of my learning journey 🚀 Started **DBMS with Shubham Sir**. @Hiteshdotcom | @piyushgarg_dev |@nirudhuuu #DBMS #SQL #LearningJourney
RajSing62691380's tweet image. Week 11 of my learning journey 🚀 Started **DBMS with Shubham Sir**. @Hiteshdotcom | @piyushgarg_dev |@nirudhuuu #DBMS #SQL #LearningJourney
RajSing62691380's tweet image. Week 11 of my learning journey 🚀 Started **DBMS with Shubham Sir**. @Hiteshdotcom | @piyushgarg_dev |@nirudhuuu #DBMS #SQL #LearningJourney
RajSing62691380's tweet image. Week 11 of my learning journey 🚀 Started **DBMS with Shubham Sir**. @Hiteshdotcom | @piyushgarg_dev |@nirudhuuu #DBMS #SQL #LearningJourney
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UttamYadav_01's profile picture. 💡 Turning Thoughts into Projects | 💻 Full-Stack Dev | 📚 DSA Enthusiast | 🚀 Helping People Learn & Build | #BuildInPublic
Uttam Yadav
 @UttamYadav_01
Nov 4

Today I learned Dijkstra’s Algorithm — the shortest path approach for weighted graphs, and explored Bellman-Ford to handle negative edges. Also revised DBMS Sharding & Clustering — mastering data distribution & scalability. 🚀 #DSA #DBMS #Coding

UttamYadav_01's tweet image. Today I learned Dijkstra’s Algorithm — the shortest path approach for weighted graphs, and explored Bellman-Ford to handle negative edges. Also revised DBMS Sharding & Clustering — mastering data distribution & scalability. 🚀 #DSA #DBMS #Coding
UttamYadav_01's tweet image. Today I learned Dijkstra’s Algorithm — the shortest path approach for weighted graphs, and explored Bellman-Ford to handle negative edges. Also revised DBMS Sharding & Clustering — mastering data distribution & scalability. 🚀 #DSA #DBMS #Coding
UttamYadav_01's tweet image. Today I learned Dijkstra’s Algorithm — the shortest path approach for weighted graphs, and explored Bellman-Ford to handle negative edges. Also revised DBMS Sharding & Clustering — mastering data distribution & scalability. 🚀 #DSA #DBMS #Coding
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jai_baradia's profile picture. Smart contract developer (EVM)
Jai Baradia
 @jai_baradia
Apr 8

Built ER Diagram for a Clinic Diagnostics Platform: - Appointment vs. Consultation logic - Dynamic Test Catalog & Prescriptions - Snapshot pricing in Payments (No data corruption!) - Normalized Schema (13 Entities) @Hiteshdotcom @nirudhuuu @piyushgarg_dev #DBMS #ChaiCode

jai_baradia's tweet image. Built ER Diagram for a Clinic Diagnostics Platform: - Appointment vs. Consultation logic - Dynamic Test Catalog & Prescriptions - Snapshot pricing in Payments (No data corruption!) - Normalized Schema (13 Entities) @Hiteshdotcom @nirudhuuu @piyushgarg_dev #DBMS #ChaiCode
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AlibabaCloud_jp's profile picture. Alibaba Cloud（アリババクラウド）日本公式アカウント 最先端のインテリジェント機能と、世界規模のAIクラウドコンピューティングネットワークを提供し、開発者にやさしいAIサービスをグローバルに展開しています🌎 #Qwen はアリババが開発した、大規模言語モデルおよびマルチモーダルAIモデルのファミリーです
Alibaba Cloud（アリババクラウド）
@AlibabaCloud_jp
Dec 19

【報道発表】アリババクラウド、ガートナー社の「Magic Quadrant™ for Cloud Database Management Systems」において6年連続で「リーダー」に選出 ⏩alibabacloud.com/blog/602747 自社開発 #DBMS 製品全般におけるサーバーレス対応など包括的なクラウドネイティブ機能や、#PolarDB

AlibabaCloud_jp's tweet image. 【報道発表】アリババクラウド、ガートナー社の「Magic Quadrant™ for Cloud Database Management Systems」において6年連続で「リーダー」に選出 ⏩alibabacloud.com/blog/602747 自社開発 #DBMS 製品全般におけるサーバーレス対応など包括的なクラウドネイティブ機能や、#PolarDB
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genlaishenshu's profile picture. 広告会社人事労務#特定社会保険労務士#中小企業診断士受験生#健康経営エキスパートアドバイザー#青学WSD36期#筑波キャリプロ7期#中国駐在経験14年#TAC宮島クラス#公認心理師#メンタルヘルス・マネジメントⅠ種#第I種衛生管理者#母校智辯和歌山と故郷和歌山を愛し、中国が大好きです！
のぶさん
 @genlaishenshu
Feb 24

おはようございます。火曜日はスタバからスタート。経営情報システム2回目のトレーニングを解いています。 #中小企業診断士試験 #経営情報システム #DBMS #SQL #正規化

genlaishenshu's tweet image. おはようございます。火曜日はスタバからスタート。経営情報システム2回目のトレーニングを解いています。 #中小企業診断士試験 #経営情報システム #DBMS #SQL #正規化
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milan_od's profile picture. an Engineer
Milan Mohapatra
 @milan_od
Apr 12

Types: • Relational → tables + relationships • Non-relational → flexible, scalable Used everywhere from small businesses to social media apps. #Database #DBMS #TechBasics

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UttamYadav_01's profile picture. 💡 Turning Thoughts into Projects | 💻 Full-Stack Dev | 📚 DSA Enthusiast | 🚀 Helping People Learn & Build | #BuildInPublic
Uttam Yadav
 @UttamYadav_01
Nov 5

Day 1 of #WinterArcChallenge ❄️ 📘 DSA: Learned Bellman-Ford algorithm revised Merge Two Linked Lists 💾 CS Fundamentals: Studied DBMS sharding, partitioning & scalable systems ⚡Revision: JavaScript basics Let’s keep pushing! 💪 #DSA #DBMS #SystemDesign #JavaScript #Coding

UttamYadav_01's tweet image. Day 1 of #WinterArcChallenge ❄️ 📘 DSA: Learned Bellman-Ford algorithm revised Merge Two Linked Lists 💾 CS Fundamentals: Studied DBMS sharding, partitioning & scalable systems ⚡Revision: JavaScript basics Let’s keep pushing! 💪 #DSA #DBMS #SystemDesign #JavaScript #Coding
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1drie5's profile picture. somehow trying to get into tech while having a lot of skill issues
iddu
 @1drie5
Apr 13

L38 (29) inner join = where your data overlaps. only returns matching rows. select c.name, o.ordername from customer c inner join orders o on c.id=o.id; tip: "join" defaults to inner join! #DBMS #SQL #Databases

1drie5's tweet image. L38 (29) inner join = where your data overlaps. only returns matching rows. select c.name, o.ordername from customer c inner join orders o on c.id=o.id; tip: "join" defaults to inner join! #DBMS #SQL #Databases
1drie5's profile picture. somehow trying to get into tech while having a lot of skill issues
iddu
 @1drie5
Apr 12

L38 (28) joins combine rows from tables via shared columns. inner = matched rows only. left/right = 1 side all + matches. full = everything from both. cross = cartesian. self = table to itself. fk not required — just matching data. #DBMS #SQL #Databases

1drie5's tweet image. L38 (28) joins combine rows from tables via shared columns. inner = matched rows only. left/right = 1 side all + matches. full = everything from both. cross = cartesian. self = table to itself. fk not required — just matching data. #DBMS #SQL #Databases
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1drie5's profile picture. somehow trying to get into tech while having a lot of skill issues
iddu
 @1drie5
Apr 12

L38 (28) joins combine rows from tables via shared columns. inner = matched rows only. left/right = 1 side all + matches. full = everything from both. cross = cartesian. self = table to itself. fk not required — just matching data. #DBMS #SQL #Databases

1drie5's tweet image. L38 (28) joins combine rows from tables via shared columns. inner = matched rows only. left/right = 1 side all + matches. full = everything from both. cross = cartesian. self = table to itself. fk not required — just matching data. #DBMS #SQL #Databases
1drie5's profile picture. somehow trying to get into tech while having a lot of skill issues
iddu
 @1drie5
Apr 11

L38 (27) the order of sql commands: how you WRITE it: 1. select 2. from 3. where 4. group by 5. having 6. order by 7. limit how the database EXECUTES it: from → where → group by → having → select → order by → limit know the difference! #DBMS #SQL #Databases

1drie5's tweet image. L38 (27) the order of sql commands: how you WRITE it: 1. select 2. from 3. where 4. group by 5. having 6. order by 7. limit how the database EXECUTES it: from → where → group by → having → select → order by → limit know the difference! #DBMS #SQL #Databases
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1drie5's profile picture. somehow trying to get into tech while having a lot of skill issues
iddu
 @1drie5
Apr 15

L38 (31) right join = all right + matches (else NULL). select c.name, o.ordername from customer c right join orders o on c.id = o.id; tip: rarely used! devs prefer flipping tables & using left joins. #DBMS #SQL #Databases

1drie5's tweet image. L38 (31) right join = all right + matches (else NULL). select c.name, o.ordername from customer c right join orders o on c.id = o.id; tip: rarely used! devs prefer flipping tables & using left joins. #DBMS #SQL #Databases
1drie5's profile picture. somehow trying to get into tech while having a lot of skill issues
iddu
 @1drie5
Apr 14

L38 (30) left join = all left + matches (else NULL) select c.name from customer c left join orders o on c.id=o.id where is null; tip: is null → 0 buys #DBMS #SQL #Databases

1drie5's tweet image. L38 (30) left join = all left + matches (else NULL) select c.name from customer c left join orders o on c.id=o.id where is null; tip: is null → 0 buys #DBMS #SQL #Databases
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1drie5's profile picture. somehow trying to get into tech while having a lot of skill issues
iddu
 @1drie5
9 h

L38 (34) self join = table joined to itself. rule: MUST use aliases to separate rows! select m.name as mentor, s.name as student from student m join student s on m.s_id = s.mentor_id; tip: best for hierarchical data. #DBMS #SQL #Databases

1drie5's tweet image. L38 (34) self join = table joined to itself. rule: MUST use aliases to separate rows! select m.name as mentor, s.name as student from student m join student s on m.s_id = s.mentor_id; tip: best for hierarchical data. #DBMS #SQL #Databases
1drie5's profile picture. somehow trying to get into tech while having a lot of skill issues
iddu
 @1drie5
Apr 17

L38 (33) cross join = the cartesian product. every row from table A pairs with every row from B (m * n). select * from cust cross join ord; tip: careful! 1,000 users × 1,000 orders = 1 million rows. mostly used to generate test data or item variations. #DBMS #SQL #Databases

1drie5's tweet image. L38 (33) cross join = the cartesian product. every row from table A pairs with every row from B (m * n). select * from cust cross join ord; tip: careful! 1,000 users × 1,000 orders = 1 million rows. mostly used to generate test data or item variations. #DBMS #SQL #Databases
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1drie5's profile picture. somehow trying to get into tech while having a lot of skill issues
iddu
 @1drie5
Apr 17

L38 (33) cross join = the cartesian product. every row from table A pairs with every row from B (m * n). select * from cust cross join ord; tip: careful! 1,000 users × 1,000 orders = 1 million rows. mostly used to generate test data or item variations. #DBMS #SQL #Databases

1drie5's tweet image. L38 (33) cross join = the cartesian product. every row from table A pairs with every row from B (m * n). select * from cust cross join ord; tip: careful! 1,000 users × 1,000 orders = 1 million rows. mostly used to generate test data or item variations. #DBMS #SQL #Databases
1drie5's profile picture. somehow trying to get into tech while having a lot of skill issues
iddu
 @1drie5
Apr 16

L38(32) full join = everything from both. MySQL lacks it! use UNION: select * from cust c left join ord o on c.id=o.id union select * from cust c right join ord o on =; #DBMS #SQL #Databases

1drie5's tweet image. L38(32) full join = everything from both. MySQL lacks it! use UNION: select * from cust c left join ord o on c.id=o.id union select * from cust c right join ord o on =; #DBMS #SQL #Databases
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AdamyaKhairwal1's profile picture. Reimagining what’s possible. Simple. Powerful. Human. Cloud Computing Resources for Startups & Individuals Visit @ https://t.co/2Z12xIonpY
Vasuki iTech
 @AdamyaKhairwal1
Apr 17

It's Finally Happening! Join us on 30th April for Live Keynotes, Dev tools and gain access to the most premium #cloud and #dbms system. Book a place: vasuki.cloud/io #x #vasukiitech #io #livekeynotes #devtools

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1drie5's profile picture. somehow trying to get into tech while having a lot of skill issues
iddu
 @1drie5
Apr 16

L38(32) full join = everything from both. MySQL lacks it! use UNION: select * from cust c left join ord o on c.id=o.id union select * from cust c right join ord o on =; #DBMS #SQL #Databases

1drie5's tweet image. L38(32) full join = everything from both. MySQL lacks it! use UNION: select * from cust c left join ord o on c.id=o.id union select * from cust c right join ord o on =; #DBMS #SQL #Databases
1drie5's profile picture. somehow trying to get into tech while having a lot of skill issues
iddu
 @1drie5
Apr 15

L38 (31) right join = all right + matches (else NULL). select c.name, o.ordername from customer c right join orders o on c.id = o.id; tip: rarely used! devs prefer flipping tables & using left joins. #DBMS #SQL #Databases

1drie5's tweet image. L38 (31) right join = all right + matches (else NULL). select c.name, o.ordername from customer c right join orders o on c.id = o.id; tip: rarely used! devs prefer flipping tables & using left joins. #DBMS #SQL #Databases
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rnsitmca8421's profile picture.
RNSITMCA
 @rnsitmca8421
Apr 16

✨ From Kernel to Query—powering future tech minds! Student Development Program @ SRS FGC 🎓 Sessions on OS, Shell & DBMS by Dr. Nagesh B S (HoD, MCA, RNSIT) 💻📊 #StudentDevelopment #DBMS #OS #RNSIT

rnsitmca8421's tweet image. ✨ From Kernel to Query—powering future tech minds! Student Development Program @ SRS FGC 🎓 Sessions on OS, Shell & DBMS by Dr. Nagesh B S (HoD, MCA, RNSIT) 💻📊 #StudentDevelopment #DBMS #OS #RNSIT
rnsitmca8421's tweet image. ✨ From Kernel to Query—powering future tech minds! Student Development Program @ SRS FGC 🎓 Sessions on OS, Shell & DBMS by Dr. Nagesh B S (HoD, MCA, RNSIT) 💻📊 #StudentDevelopment #DBMS #OS #RNSIT
rnsitmca8421's tweet image. ✨ From Kernel to Query—powering future tech minds! Student Development Program @ SRS FGC 🎓 Sessions on OS, Shell & DBMS by Dr. Nagesh B S (HoD, MCA, RNSIT) 💻📊 #StudentDevelopment #DBMS #OS #RNSIT
rnsitmca8421's tweet image. ✨ From Kernel to Query—powering future tech minds! Student Development Program @ SRS FGC 🎓 Sessions on OS, Shell & DBMS by Dr. Nagesh B S (HoD, MCA, RNSIT) 💻📊 #StudentDevelopment #DBMS #OS #RNSIT
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1drie5's profile picture. somehow trying to get into tech while having a lot of skill issues
iddu
 @1drie5
Apr 15

L38 (31) right join = all right + matches (else NULL). select c.name, o.ordername from customer c right join orders o on c.id = o.id; tip: rarely used! devs prefer flipping tables & using left joins. #DBMS #SQL #Databases

1drie5's tweet image. L38 (31) right join = all right + matches (else NULL). select c.name, o.ordername from customer c right join orders o on c.id = o.id; tip: rarely used! devs prefer flipping tables & using left joins. #DBMS #SQL #Databases
1drie5's profile picture. somehow trying to get into tech while having a lot of skill issues
iddu
 @1drie5
Apr 14

L38 (30) left join = all left + matches (else NULL) select c.name from customer c left join orders o on c.id=o.id where is null; tip: is null → 0 buys #DBMS #SQL #Databases

1drie5's tweet image. L38 (30) left join = all left + matches (else NULL) select c.name from customer c left join orders o on c.id=o.id where is null; tip: is null → 0 buys #DBMS #SQL #Databases
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MadeSimpleMSSQL's profile picture.
MadeSimpleMSSQL
 @MadeSimpleMSSQL
Apr 15

🚀Ready to crack your SQL Server interview? Start learning the real Interview Questions Series asked in top companies. Visit our channel now and level up your skills! youtube.com/shorts/z_lMsIV… #dbms #Data #sql #sqldatabase #sqldba #DBA #DBAProgram #madesimplemssql #Analyticss

MadeSimpleMSSQL's tweet card. SQL Server Interview Questions Part - 4 | #sql #education #coding |...

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SQL Server Interview Questions Part - 4 | #sql #education #coding |...

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1drie5's profile picture. somehow trying to get into tech while having a lot of skill issues
iddu
 @1drie5
Apr 14

L38 (30) left join = all left + matches (else NULL) select c.name from customer c left join orders o on c.id=o.id where is null; tip: is null → 0 buys #DBMS #SQL #Databases

1drie5's tweet image. L38 (30) left join = all left + matches (else NULL) select c.name from customer c left join orders o on c.id=o.id where is null; tip: is null → 0 buys #DBMS #SQL #Databases
1drie5's profile picture. somehow trying to get into tech while having a lot of skill issues
iddu
 @1drie5
Apr 13

L38 (29) inner join = where your data overlaps. only returns matching rows. select c.name, o.ordername from customer c inner join orders o on c.id=o.id; tip: "join" defaults to inner join! #DBMS #SQL #Databases

1drie5's tweet image. L38 (29) inner join = where your data overlaps. only returns matching rows. select c.name, o.ordername from customer c inner join orders o on c.id=o.id; tip: "join" defaults to inner join! #DBMS #SQL #Databases
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RealTimeDBMS's profile picture. eXtremeDB/rt is the 1st-and so far only-deterministic embedded DBMS for mission & safety critical hard real-time applications. Now RTOS developers have options!
RealTimeDBMS
 @RealTimeDBMS
Apr 13

Why did embedded world 2026 honor eXtremeDB/rt with the embedded award: Software? #eXtremeDB/rt is the only COTS hard real time #DBMS. It also eliminates the flash file system and reducing write amplification. Learn more t.ly/jnUSB #EmbeddedSystems #flashmemory

RealTimeDBMS's tweet image. Why did embedded world 2026 honor eXtremeDB/rt with the embedded award: Software? #eXtremeDB/rt is the only COTS hard real time #DBMS. It also eliminates the flash file system and reducing write amplification. Learn more t.ly/jnUSB #EmbeddedSystems #flashmemory
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1drie5's profile picture. somehow trying to get into tech while having a lot of skill issues
iddu
 @1drie5
Apr 13

L38 (29) inner join = where your data overlaps. only returns matching rows. select c.name, o.ordername from customer c inner join orders o on c.id=o.id; tip: "join" defaults to inner join! #DBMS #SQL #Databases

1drie5's tweet image. L38 (29) inner join = where your data overlaps. only returns matching rows. select c.name, o.ordername from customer c inner join orders o on c.id=o.id; tip: "join" defaults to inner join! #DBMS #SQL #Databases
1drie5's profile picture. somehow trying to get into tech while having a lot of skill issues
iddu
 @1drie5
Apr 12

L38 (28) joins combine rows from tables via shared columns. inner = matched rows only. left/right = 1 side all + matches. full = everything from both. cross = cartesian. self = table to itself. fk not required — just matching data. #DBMS #SQL #Databases

1drie5's tweet image. L38 (28) joins combine rows from tables via shared columns. inner = matched rows only. left/right = 1 side all + matches. full = everything from both. cross = cartesian. self = table to itself. fk not required — just matching data. #DBMS #SQL #Databases
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Rohan_269's profile picture. Know your Direction.
Rohan
 @Rohan_269
Apr 13

Starting DBMS playlist by CodeHelp... #CodeHelp #DBMS

Rohan_269's tweet image. Starting DBMS playlist by CodeHelp... #CodeHelp #DBMS
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Shriyansh_0210's profile picture.
Shriyansh Agarwal
 @Shriyansh_0210
Apr 12

Week 12 Sunday Class From ERD → DB Models → API Built a full IPL backend flow and finally saw how design impacts everything Good schema = clean backend Bad schema = struggle This one clicked 💡 #Backend #SystemDesign #DBMS #chaicode @surajtwt_

Shriyansh_0210's tweet image. Week 12 Sunday Class From ERD → DB Models → API Built a full IPL backend flow and finally saw how design impacts everything Good schema = clean backend Bad schema = struggle This one clicked 💡 #Backend #SystemDesign #DBMS #chaicode @surajtwt_
Shriyansh_0210's tweet image. Week 12 Sunday Class From ERD → DB Models → API Built a full IPL backend flow and finally saw how design impacts everything Good schema = clean backend Bad schema = struggle This one clicked 💡 #Backend #SystemDesign #DBMS #chaicode @surajtwt_
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_kumar_pratham's profile picture. MERN STACK Developer. DSA.
Pratham Kumar
 @_kumar_pratham
Apr 12

Built a full IPL management system from scratch, starting with DataBase design, converting it into clean database models, then implementing routes and connecting the complete backend flow . @surajtwt_ @ChaiCodeHQ @nirudhuuu #Database #DBMS #ChaiCode #BackendDevelopment #ERD #API

_kumar_pratham's tweet image. Built a full IPL management system from scratch, starting with DataBase design, converting it into clean database models, then implementing routes and connecting the complete backend flow . @surajtwt_ @ChaiCodeHQ @nirudhuuu #Database #DBMS #ChaiCode #BackendDevelopment #ERD #API
_kumar_pratham's tweet image. Built a full IPL management system from scratch, starting with DataBase design, converting it into clean database models, then implementing routes and connecting the complete backend flow . @surajtwt_ @ChaiCodeHQ @nirudhuuu #Database #DBMS #ChaiCode #BackendDevelopment #ERD #API
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Coder_dnano's profile picture. Hi, I am learning Web Development and trying to figure out how things work.
Dnyaneshwar More
 @Coder_dnano
Apr 12

Today’s cohort session → IPL management system ERD → entities, relations, embedding/references, junction tables → models + DB structuring → routes + backend flow from diagram → working backend #chaicode #backend #DBMS

Coder_dnano's tweet image. Today’s cohort session → IPL management system ERD → entities, relations, embedding/references, junction tables → models + DB structuring → routes + backend flow from diagram → working backend #chaicode #backend #DBMS
Coder_dnano's tweet image. Today’s cohort session → IPL management system ERD → entities, relations, embedding/references, junction tables → models + DB structuring → routes + backend flow from diagram → working backend #chaicode #backend #DBMS
Coder_dnano's tweet image. Today’s cohort session → IPL management system ERD → entities, relations, embedding/references, junction tables → models + DB structuring → routes + backend flow from diagram → working backend #chaicode #backend #DBMS
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1drie5's profile picture. somehow trying to get into tech while having a lot of skill issues
iddu
 @1drie5
Apr 12

L38 (28) joins combine rows from tables via shared columns. inner = matched rows only. left/right = 1 side all + matches. full = everything from both. cross = cartesian. self = table to itself. fk not required — just matching data. #DBMS #SQL #Databases

1drie5's tweet image. L38 (28) joins combine rows from tables via shared columns. inner = matched rows only. left/right = 1 side all + matches. full = everything from both. cross = cartesian. self = table to itself. fk not required — just matching data. #DBMS #SQL #Databases
1drie5's profile picture. somehow trying to get into tech while having a lot of skill issues
iddu
 @1drie5
Apr 11

L38 (27) the order of sql commands: how you WRITE it: 1. select 2. from 3. where 4. group by 5. having 6. order by 7. limit how the database EXECUTES it: from → where → group by → having → select → order by → limit know the difference! #DBMS #SQL #Databases

1drie5's tweet image. L38 (27) the order of sql commands: how you WRITE it: 1. select 2. from 3. where 4. group by 5. having 6. order by 7. limit how the database EXECUTES it: from → where → group by → having → select → order by → limit know the difference! #DBMS #SQL #Databases
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BhavayNagpal1's profile picture. Pushing to prod on friday to assert dominance. 🔗 https://t.co/6EX011iQLR
Bhavay
 @BhavayNagpal1
Apr 12

In today's class we designed a complete IPL management system from scratch. Started with ER diagram - entities, relations, junction tables. Converted it into models and structured database properly. Then moved to routes and actual backend flow @nirudhuuu #DBMS #ChaiCode

BhavayNagpal1's tweet image. In today's class we designed a complete IPL management system from scratch. Started with ER diagram - entities, relations, junction tables. Converted it into models and structured database properly. Then moved to routes and actual backend flow @nirudhuuu #DBMS #ChaiCode
BhavayNagpal1's tweet image. In today's class we designed a complete IPL management system from scratch. Started with ER diagram - entities, relations, junction tables. Converted it into models and structured database properly. Then moved to routes and actual backend flow @nirudhuuu #DBMS #ChaiCode
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rachit26227444's profile picture. CSE student | Learning Web Dev & Python Exploring AI/ML through projects Building in public
rachit
 @rachit26227444
Apr 12

Designed a complete IPL management system from scratch today Started with ER diagram → entities, relations, junction tables Converted it into models and structured database properly Then moved to routes and actual backend flow #DBMS #ChaiCode @nirudhuuu @ChaiCodeHQ

rachit26227444's tweet image. Designed a complete IPL management system from scratch today Started with ER diagram → entities, relations, junction tables Converted it into models and structured database properly Then moved to routes and actual backend flow #DBMS #ChaiCode @nirudhuuu @ChaiCodeHQ
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RajSing62691380's profile picture. Hey !
Raj Singh
 @RajSing62691380
Apr 9

Week 11 of my learning journey 🚀 Started **DBMS with Shubham Sir**. @Hiteshdotcom | @piyushgarg_dev |@nirudhuuu #DBMS #SQL #LearningJourney

RajSing62691380's tweet image. Week 11 of my learning journey 🚀 Started **DBMS with Shubham Sir**. @Hiteshdotcom | @piyushgarg_dev |@nirudhuuu #DBMS #SQL #LearningJourney
RajSing62691380's tweet image. Week 11 of my learning journey 🚀 Started **DBMS with Shubham Sir**. @Hiteshdotcom | @piyushgarg_dev |@nirudhuuu #DBMS #SQL #LearningJourney
RajSing62691380's tweet image. Week 11 of my learning journey 🚀 Started **DBMS with Shubham Sir**. @Hiteshdotcom | @piyushgarg_dev |@nirudhuuu #DBMS #SQL #LearningJourney
RajSing62691380's tweet image. Week 11 of my learning journey 🚀 Started **DBMS with Shubham Sir**. @Hiteshdotcom | @piyushgarg_dev |@nirudhuuu #DBMS #SQL #LearningJourney
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devwithjay's profile picture. Ui » Ux » Web Dev
Jay Kadlag
 @devwithjay
Apr 4

𝗗𝗮𝘁𝗮 𝘀𝗶𝗱𝗲 𝗯𝗲𝗴𝗶𝗻𝘀 📊 • Creating databases and tables • Inserting and selecting data • Filtering records • UPDATE table • DELETE with WHERE • ALTER TABLE operations • DISTINCT, sorting, LIMIT, OFFSET • Aggregations • GROUP BY #DBMS #SQL #Backend #ChaiCode

devwithjay's tweet image. 𝗗𝗮𝘁𝗮 𝘀𝗶𝗱𝗲 𝗯𝗲𝗴𝗶𝗻𝘀 📊 • Creating databases and tables • Inserting and selecting data • Filtering records • UPDATE table • DELETE with WHERE • ALTER TABLE operations • DISTINCT, sorting, LIMIT, OFFSET • Aggregations • GROUP BY #DBMS #SQL #Backend #ChaiCode
devwithjay's tweet image. 𝗗𝗮𝘁𝗮 𝘀𝗶𝗱𝗲 𝗯𝗲𝗴𝗶𝗻𝘀 📊 • Creating databases and tables • Inserting and selecting data • Filtering records • UPDATE table • DELETE with WHERE • ALTER TABLE operations • DISTINCT, sorting, LIMIT, OFFSET • Aggregations • GROUP BY #DBMS #SQL #Backend #ChaiCode
devwithjay's tweet image. 𝗗𝗮𝘁𝗮 𝘀𝗶𝗱𝗲 𝗯𝗲𝗴𝗶𝗻𝘀 📊 • Creating databases and tables • Inserting and selecting data • Filtering records • UPDATE table • DELETE with WHERE • ALTER TABLE operations • DISTINCT, sorting, LIMIT, OFFSET • Aggregations • GROUP BY #DBMS #SQL #Backend #ChaiCode
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devwithjay's profile picture. Ui » Ux » Web Dev
Jay Kadlag
 @devwithjay
Apr 12

𝗙𝗿𝗼𝗺 𝗘𝗥𝗗 𝘁𝗼 𝗔𝗣𝗜 🏏 Designed a complete IPL management system from scratch today Started with ER diagram → entities, relations, junction tables Converted it into models and structured database properly Then moved to routes and actual backend flow #DBMS #ChaiCode

devwithjay's tweet image. 𝗙𝗿𝗼𝗺 𝗘𝗥𝗗 𝘁𝗼 𝗔𝗣𝗜 🏏 Designed a complete IPL management system from scratch today Started with ER diagram → entities, relations, junction tables Converted it into models and structured database properly Then moved to routes and actual backend flow #DBMS #ChaiCode
devwithjay's tweet image. 𝗙𝗿𝗼𝗺 𝗘𝗥𝗗 𝘁𝗼 𝗔𝗣𝗜 🏏 Designed a complete IPL management system from scratch today Started with ER diagram → entities, relations, junction tables Converted it into models and structured database properly Then moved to routes and actual backend flow #DBMS #ChaiCode
devwithjay's tweet image. 𝗙𝗿𝗼𝗺 𝗘𝗥𝗗 𝘁𝗼 𝗔𝗣𝗜 🏏 Designed a complete IPL management system from scratch today Started with ER diagram → entities, relations, junction tables Converted it into models and structured database properly Then moved to routes and actual backend flow #DBMS #ChaiCode
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devwithjay's profile picture. Ui » Ux » Web Dev
Jay Kadlag
 @devwithjay
Apr 5

𝗝𝗼𝗶𝗻𝘀 & 𝗜𝗻𝗱𝗲𝘅𝗶𝗻𝗴 ⚡ Today’s class went deeper into SQL, joins, foreign keys, & constraints. Also explored indexing and how databases optimize queries behind the scenes. Designed an Instagram-like system using ER diagrams. #DBMS #SQL #Backend #ChaiCode

devwithjay's tweet image. 𝗝𝗼𝗶𝗻𝘀 & 𝗜𝗻𝗱𝗲𝘅𝗶𝗻𝗴 ⚡ Today’s class went deeper into SQL, joins, foreign keys, & constraints. Also explored indexing and how databases optimize queries behind the scenes. Designed an Instagram-like system using ER diagrams. #DBMS #SQL #Backend #ChaiCode
devwithjay's tweet image. 𝗝𝗼𝗶𝗻𝘀 & 𝗜𝗻𝗱𝗲𝘅𝗶𝗻𝗴 ⚡ Today’s class went deeper into SQL, joins, foreign keys, & constraints. Also explored indexing and how databases optimize queries behind the scenes. Designed an Instagram-like system using ER diagrams. #DBMS #SQL #Backend #ChaiCode
devwithjay's tweet image. 𝗝𝗼𝗶𝗻𝘀 & 𝗜𝗻𝗱𝗲𝘅𝗶𝗻𝗴 ⚡ Today’s class went deeper into SQL, joins, foreign keys, & constraints. Also explored indexing and how databases optimize queries behind the scenes. Designed an Instagram-like system using ER diagrams. #DBMS #SQL #Backend #ChaiCode
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kidehen's profile picture. Founder & CEO, OpenLink Software. 🔗 https://t.co/sTt5T5d1uA 🔗 https://t.co/VGVHGUGEHq 🔗 https://t.co/owcnsohhvA 🔗 https://t.co/FtJLPA3IDl
Kingsley Uyi Idehen
@kidehen
Jul 27, 2024

What are counterfeit Knowledge Graphs? Please read: linkedin.com/pulse/counterf… #KnowledgeGraph has become a confusing term that confuses unsuspecting end-users and integrators. Even more so in the age of #GenAI. #DBMS #LPG #RDBMS #Issues #CDO #CIO #CAIO #CMO #AI #RAG #GraphRAG

kidehen's tweet image. What are counterfeit Knowledge Graphs? Please read: linkedin.com/pulse/counterf… #KnowledgeGraph has become a confusing term that confuses unsuspecting end-users and integrators. Even more so in the age of #GenAI. #DBMS #LPG #RDBMS #Issues #CDO #CIO #CAIO #CMO #AI #RAG #GraphRAG
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UttamYadav_01's profile picture. 💡 Turning Thoughts into Projects | 💻 Full-Stack Dev | 📚 DSA Enthusiast | 🚀 Helping People Learn & Build | #BuildInPublic
Uttam Yadav
 @UttamYadav_01
Nov 5

Day 1 of #WinterArcChallenge ❄️ 📘 DSA: Learned Bellman-Ford algorithm revised Merge Two Linked Lists 💾 CS Fundamentals: Studied DBMS sharding, partitioning & scalable systems ⚡Revision: JavaScript basics Let’s keep pushing! 💪 #DSA #DBMS #SystemDesign #JavaScript #Coding

UttamYadav_01's tweet image. Day 1 of #WinterArcChallenge ❄️ 📘 DSA: Learned Bellman-Ford algorithm revised Merge Two Linked Lists 💾 CS Fundamentals: Studied DBMS sharding, partitioning & scalable systems ⚡Revision: JavaScript basics Let’s keep pushing! 💪 #DSA #DBMS #SystemDesign #JavaScript #Coding
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tiwari_pee28336's profile picture. 💻 Web Development Learner ⚡ JavaScript | TypeScript | Backend 🚀 Building projects & sharing my dev journey in public 📈 Learning something new every day
Peeyush Tiwari
 @tiwari_pee28336
Apr 6

🚀 ER Diagram Assignment Done! Designed an Instagram-like thrift database — focused on structure, relationships & scalability. Grateful for the guidance 🙌 @Hiteshdotcom sir,@piyushgarg_dev @yntpdotme @nirudhuuu @surajtwt_ @devwithjay @ChaiCodeHQ #DBMS #SQL #LearningInPublic

tiwari_pee28336's tweet image. 🚀 ER Diagram Assignment Done! Designed an Instagram-like thrift database — focused on structure, relationships & scalability. Grateful for the guidance 🙌 @Hiteshdotcom sir,@piyushgarg_dev @yntpdotme @nirudhuuu @surajtwt_ @devwithjay @ChaiCodeHQ #DBMS #SQL #LearningInPublic
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RealTimeDBMS's profile picture. eXtremeDB/rt is the 1st-and so far only-deterministic embedded DBMS for mission & safety critical hard real-time applications. Now RTOS developers have options!
RealTimeDBMS
 @RealTimeDBMS
Nov 18

Read the insightful new article "Engineering Real-Time: Lessons Learned While Chasing Determinism" part 1 in @embedded_comp t.ly/oJbaX #realtimedata #DBMS #deterministicdatabase

RealTimeDBMS's tweet image. Read the insightful new article "Engineering Real-Time: Lessons Learned While Chasing Determinism" part 1 in @embedded_comp t.ly/oJbaX #realtimedata #DBMS #deterministicdatabase
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jai_baradia's profile picture. Smart contract developer (EVM)
Jai Baradia
 @jai_baradia
Apr 12

IPL mangement DB Design done @surajtwt_ sir and @nirudhuuu sir was thinking to go deep but as said to make a simple desing so here it is. #DBMS #chaicode #Backend

jai_baradia's tweet image. IPL mangement DB Design done @surajtwt_ sir and @nirudhuuu sir was thinking to go deep but as said to make a simple desing so here it is. #DBMS #chaicode #Backend
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genlaishenshu's profile picture. 広告会社人事労務#特定社会保険労務士#中小企業診断士受験生#健康経営エキスパートアドバイザー#青学WSD36期#筑波キャリプロ7期#中国駐在経験14年#TAC宮島クラス#公認心理師#メンタルヘルス・マネジメントⅠ種#第I種衛生管理者#母校智辯和歌山と故郷和歌山を愛し、中国が大好きです！
のぶさん
 @genlaishenshu
Feb 24

おはようございます。火曜日はスタバからスタート。経営情報システム2回目のトレーニングを解いています。 #中小企業診断士試験 #経営情報システム #DBMS #SQL #正規化

genlaishenshu's tweet image. おはようございます。火曜日はスタバからスタート。経営情報システム2回目のトレーニングを解いています。 #中小企業診断士試験 #経営情報システム #DBMS #SQL #正規化
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AlibabaCloud_jp's profile picture. Alibaba Cloud（アリババクラウド）日本公式アカウント 最先端のインテリジェント機能と、世界規模のAIクラウドコンピューティングネットワークを提供し、開発者にやさしいAIサービスをグローバルに展開しています🌎 #Qwen はアリババが開発した、大規模言語モデルおよびマルチモーダルAIモデルのファミリーです
Alibaba Cloud（アリババクラウド）
@AlibabaCloud_jp
Dec 19

【報道発表】アリババクラウド、ガートナー社の「Magic Quadrant™ for Cloud Database Management Systems」において6年連続で「リーダー」に選出 ⏩alibabacloud.com/blog/602747 自社開発 #DBMS 製品全般におけるサーバーレス対応など包括的なクラウドネイティブ機能や、#PolarDB

AlibabaCloud_jp's tweet image. 【報道発表】アリババクラウド、ガートナー社の「Magic Quadrant™ for Cloud Database Management Systems」において6年連続で「リーダー」に選出 ⏩alibabacloud.com/blog/602747 自社開発 #DBMS 製品全般におけるサーバーレス対応など包括的なクラウドネイティブ機能や、#PolarDB
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RealTimeDBMS's profile picture. eXtremeDB/rt is the 1st-and so far only-deterministic embedded DBMS for mission & safety critical hard real-time applications. Now RTOS developers have options!
RealTimeDBMS
 @RealTimeDBMS
Apr 13

Why did embedded world 2026 honor eXtremeDB/rt with the embedded award: Software? #eXtremeDB/rt is the only COTS hard real time #DBMS. It also eliminates the flash file system and reducing write amplification. Learn more t.ly/jnUSB #EmbeddedSystems #flashmemory

RealTimeDBMS's tweet image. Why did embedded world 2026 honor eXtremeDB/rt with the embedded award: Software? #eXtremeDB/rt is the only COTS hard real time #DBMS. It also eliminates the flash file system and reducing write amplification. Learn more t.ly/jnUSB #EmbeddedSystems #flashmemory
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RealTimeDBMS's profile picture. eXtremeDB/rt is the 1st-and so far only-deterministic embedded DBMS for mission & safety critical hard real-time applications. Now RTOS developers have options!
RealTimeDBMS
 @RealTimeDBMS
Feb 5

We invite you to review our research & articles about *hard* real-time #DBMS. If you believe that something on this page needs to be changed, or if you have something to add, please let us know in the link on the page. t.ly/1HqqO #RealTimeData #RTOS #EmbeddedSystems

RealTimeDBMS's tweet image. We invite you to review our research & articles about *hard* real-time #DBMS. If you believe that something on this page needs to be changed, or if you have something to add, please let us know in the link on the page. t.ly/1HqqO #RealTimeData #RTOS #EmbeddedSystems
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Jatin_17824's profile picture. Building Gusion | Full-Stack Dev (MERN, Next.js) | CSE ’26 @ Panjab University
Jatin Sood
 @Jatin_17824
Apr 4

𝗗𝗮𝘁𝗮 𝘀𝗶𝗱𝗲 𝗯𝗲𝗴𝗶𝗻𝘀 📊 • Creating databases and tables • Inserting and selecting data • Filtering records • UPDATE table • DELETE with WHERE • ALTER TABLE operations • DISTINCT, sorting, LIMIT, OFFSET • Aggregations • GROUP BY #DBMS #SQL #Backend #ChaiCode

Jatin_17824's tweet image. 𝗗𝗮𝘁𝗮 𝘀𝗶𝗱𝗲 𝗯𝗲𝗴𝗶𝗻𝘀 📊 • Creating databases and tables • Inserting and selecting data • Filtering records • UPDATE table • DELETE with WHERE • ALTER TABLE operations • DISTINCT, sorting, LIMIT, OFFSET • Aggregations • GROUP BY #DBMS #SQL #Backend #ChaiCode
Jatin_17824's tweet image. 𝗗𝗮𝘁𝗮 𝘀𝗶𝗱𝗲 𝗯𝗲𝗴𝗶𝗻𝘀 📊 • Creating databases and tables • Inserting and selecting data • Filtering records • UPDATE table • DELETE with WHERE • ALTER TABLE operations • DISTINCT, sorting, LIMIT, OFFSET • Aggregations • GROUP BY #DBMS #SQL #Backend #ChaiCode
Jatin_17824's tweet image. 𝗗𝗮𝘁𝗮 𝘀𝗶𝗱𝗲 𝗯𝗲𝗴𝗶𝗻𝘀 📊 • Creating databases and tables • Inserting and selecting data • Filtering records • UPDATE table • DELETE with WHERE • ALTER TABLE operations • DISTINCT, sorting, LIMIT, OFFSET • Aggregations • GROUP BY #DBMS #SQL #Backend #ChaiCode
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UttamYadav_01's profile picture. 💡 Turning Thoughts into Projects | 💻 Full-Stack Dev | 📚 DSA Enthusiast | 🚀 Helping People Learn & Build | #BuildInPublic
Uttam Yadav
 @UttamYadav_01
Nov 4

Today I learned Dijkstra’s Algorithm — the shortest path approach for weighted graphs, and explored Bellman-Ford to handle negative edges. Also revised DBMS Sharding & Clustering — mastering data distribution & scalability. 🚀 #DSA #DBMS #Coding

UttamYadav_01's tweet image. Today I learned Dijkstra’s Algorithm — the shortest path approach for weighted graphs, and explored Bellman-Ford to handle negative edges. Also revised DBMS Sharding & Clustering — mastering data distribution & scalability. 🚀 #DSA #DBMS #Coding
UttamYadav_01's tweet image. Today I learned Dijkstra’s Algorithm — the shortest path approach for weighted graphs, and explored Bellman-Ford to handle negative edges. Also revised DBMS Sharding & Clustering — mastering data distribution & scalability. 🚀 #DSA #DBMS #Coding
UttamYadav_01's tweet image. Today I learned Dijkstra’s Algorithm — the shortest path approach for weighted graphs, and explored Bellman-Ford to handle negative edges. Also revised DBMS Sharding & Clustering — mastering data distribution & scalability. 🚀 #DSA #DBMS #Coding
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1drie5's profile picture. somehow trying to get into tech while having a lot of skill issues
iddu
 @1drie5
Apr 7

L38 (23) aggregate functions = summarize rows into 1 value. > count() — total rows > sum() — column total > avg() — average > min() — smallest > max() — largest select count(*), sum(salary), avg(salary), min(salary), max(salary) from employees; #DBMS #SQL #Databases

1drie5's tweet image. L38 (23) aggregate functions = summarize rows into 1 value. > count() — total rows > sum() — column total > avg() — average > min() — smallest > max() — largest select count(*), sum(salary), avg(salary), min(salary), max(salary) from employees; #DBMS #SQL #Databases
1drie5's profile picture. somehow trying to get into tech while having a lot of skill issues
iddu
 @1drie5
Apr 6

L38 (22) sql clauses control data flow: > where = filter rows. select * from emp where age > 20; > order by = sort (asc/desc). select * from emp order by salary desc; > limit = restrict count. select * from emp limit 5; combine to find "top n" records! #DBMS #SQL #Databases

1drie5's tweet image. L38 (22) sql clauses control data flow: > where = filter rows. select * from emp where age > 20; > order by = sort (asc/desc). select * from emp order by salary desc; > limit = restrict count. select * from emp limit 5; combine to find "top n" records! #DBMS #SQL #Databases
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SaahilxRajput's profile picture. 20 Full Stack Web Developer | MERN Stack | WebRTC | Next.js | TypeScript | Framer-motion | GSAP | Web Socket | Tailwind CSS
Sahil Rajput
 @SaahilxRajput
Mar 15

Starting my DBMS learning journey today. 📚 Let’s see how much time it takes me to complete this video by @lovebabbar3 and understand the core concepts properly. Consistency mode: ON 🚀 #DBMS #LearningInPublic #100DaysOfCode #CSStudents

SaahilxRajput's tweet image. Starting my DBMS learning journey today. 📚 Let’s see how much time it takes me to complete this video by @lovebabbar3 and understand the core concepts properly. Consistency mode: ON 🚀 #DBMS #LearningInPublic #100DaysOfCode #CSStudents
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