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Posts with #DatabasePerformance

#DatabasePerformance

Public posts on X that use #DatabasePerformance.

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  2. Percona✓@Percona
    Can thread pooling speed up #MySQL? In Percona's tests, well-tuned pooling delivered nearly 18x higher throughput in an I/O-bound workload. Read about why configuration matters: #DatabasePerformance #OpenSource
    023281
  4. Percona✓@Percona
    What does MySQL 9.7 LTS bring to the table? Anil Joshi covers Group Replication monitoring, auto-eviction and rejoin, up-to-date primary elections, JSON duality views and Hypergraph Optimizer. Explore: #MySQL #DatabasePerformance #OpenSource #Databases
    002369
  5. prod42net@prod42net
    "Understand how PostgreSQL manages memory and troubleshoot low free-memory scenarios with insights from Adam Furmanek's blog post. Optimize your memory configuration for peak database performance. #PostgreSQL #MemoryManagement #DatabasePerformance"
    102127
  6. SolarWinds@solarwinds
    Migrating SAP HANA to the cloud splits your visibility between on-prem and cloud tools. SolarWinds DPA reads wait times the same way on both sides, so you catch regressions before users do. See how → #SolarWinds #SAPHANA #DatabasePerformance
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    012322
  7. MySQL@mysql_2023
    MySQL Developers 🤔 Your query is running slowly. What do you check FIRST? A) Add an INDEX B) Run EXPLAIN C) Rewrite the query D) Check server resources Choose wisely! ⚡ #MySQL #DatabasePerformance
    00010
  9. ECO@EastCoastOracle
    Get ready for a deep dive into Oracle performance tuning at #ECO2025! Roger Cornejo of @Accenture will show how to go beyond canned AWR reports using SQL to uncover hidden performance issues and think like a proactive performance engineer. #Oracle #DatabasePerformance #AWR
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    00257
  12. C.A.P@cap_ai1
    Day 19: Optimized database queries to improve data retrieval speed and system efficiency. Implemented indexing and caching strategies, reducing response time and enhancing the overall performance of our application. #DatabasePerformance #DataRetrieval #MachineLearning
    00284
  13. Roger Cornejo@OracleDBTuning
    In the latest "Taming the AWR Tsunami" post, we explore troubleshooting logon storms and session leaking in Oracle databases. Learn how to identify and resolve these performance issues using AWR metrics and other sources. #Oracle #AWR #DatabasePerformance
    015211
  14. Bella@bella_greg17839
    Database performance is not one number. Write path, compression, latest-value reads, long-range scans, and aggregations all matter differently. Small design choices at the data layer become big operational habits. #DatabasePerformance #TimeSeries
    0004
  16. Luca Canali@LucaCanaliDB
    Just used PerfSheet4 to create a performance graph from our Oracle production DBs and suddenly realized the tool is now a decade old! #Oracle #DatabasePerformance + kudos to @TanelPoder for the original PerfSheet implementation and ideas.
    2381.1K
  17. Rick Houlihan✓@houlihan_rick
    Performance cliffs are bad. Off-row storage is one of them. RDBMS splits large rows. In PostgreSQL this happens at ~2KB. Step over that line and it gets expensive fast. If you have big items, l use the right tool for the job. @MongoDB #NoSQL
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    00115.7K
  18. Pinal Dave✓@pinaldave
    Here’s the most common conversation I have with clients who sign up for my Comprehensive Database Performance Health Check. From sleepy sloth 🦥 to sprinting cheetah 🐆 — let's go.👇
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    104628
  19. Pinal Dave✓@pinaldave
    @pinaldave
    Client: I'm in! What’s next? Me: ✉️ Send a quick summary of issues + SQL Server version 📅 I send time slots + pricing 🔗 We meet on Zoom & tune your server From 🦥 to 🐆 — let’s go.
    102351
  23. Dev Ittycheria✓@dittycheria
    While PostgreSQL touts JSON support, remember that support doesn't guarantee performance. Performance will plummet when crossing certain thresholds, like the 2KB row size in PostgreSQL. #DatabasePerformance
    Rick Houlihan @houlihan_rick
    Performance cliffs are bad. Off-row storage is one of them. RDBMS splits large rows. In PostgreSQL this happens at ~2KB. Step over that line and it gets expensive fast. If you have big items, l use the right tool for the job. @MongoDB #NoSQL
    12283.6K
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