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Percona Monitoring and Management 2 Scaling and Capacity Planning

Percona

But as companies grow and see more demand for their databases, we need to ensure that PMM also remains scalable so you don’t need to worry about its performance while tending to the rest of your environment. VictoriaMetrics maintains an in-memory cache for mapping active time series into internal series IDs.

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How to Assess MySQL Performance

HammerDB

Therefore, before we attempt to measure our database performance, we should know the system or cloud instance to be tested in detail. Benchmarking the target Two of the more popular database benchmarks for MySQL are HammerDB and sysbench. Operating System: Ubuntu 22.04 Operating System: Ubuntu 22.04

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PostgreSQL Performance Tuning: Optimizing Database Parameters for Maximum Efficiency

Percona

It is primarily the responsibility of the database administrator or developer to tune PostgreSQL according to their system’s workload. Connection pooling: Minimizing connection overhead and improving response times for frequently accessed data by implementing mechanisms for connection pooling and caching strategies.

Tuning 52
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MySQL Performance Tuning 101: Key Tips to Improve MySQL Database Performance

Percona

Enhanced User Experience Whether you operate an e-commerce platform, a content management system, or any other application reliant on MySQL, users will notice and appreciate the improved speed and responsiveness. Resource contention emerges when multiple database operations vie for the same system resources simultaneously.

Tuning 52
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Five Data-Loading Patterns To Improve Frontend Performance

Smashing Magazine

On your first try, you can use it as a benchmark for optimizations later. On design systems, UX, web performance and CSS/JS. Active Memory Caching. When you want to get data that you already had quickly, you need to do cachingcaching stores data that a user recently retrieved. Caching Schemes.

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Choosing a cloud DBMS: architectures and tradeoffs

The Morning Paper

use the TPC-H benchmark to assess Redshift, Redshift Spectrum, Athena, Presto, Hive, and Vertica to find out what works best and the trade-offs involved. We focused on OLAP-oriented parallel data warehouse products available for AWS and restricted our attention to commercially available systems. Key findings. Query restrictions.

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Towards multiverse databases

The Morning Paper

Specifically, scalable, parallel streaming dataflow computing systems now support partially-stateful and dynamically-changing dataflows. The amount of computation required on a base update can be reduced by sharing computation and cached data between universes. Recent research has provided this missing key primitive.