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PostgreSQL Performance Tuning: Optimizing Database Parameters for Maximum Efficiency

Percona

Out of the box, the default PostgreSQL configuration is not tuned for any particular workload. It is primarily the responsibility of the database administrator or developer to tune PostgreSQL according to their system’s workload. What is PostgreSQL performance tuning? Why is PostgreSQL performance tuning important?

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

Percona

While there is no magic bullet for MySQL performance tuning, there are a few areas that can be focused on upfront that can dramatically improve the performance of your MySQL installation. What are the Benefits of MySQL Performance Tuning? A finely tuned database processes queries more efficiently, leading to swifter results.

Tuning 52
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How To Scale a Single-Host PostgreSQL Database With Citus

Percona

Rather than listing the concepts, function calls, etc, available in Citus, which frankly is a bit boring, I’m going to explore scaling out a database system starting with a single host. And now, execute the benchmark: -- execute the following on the coordinator node pgbench -c 20 -j 3 -T 60 -P 3 pgbench The results are not pretty.

Database 108
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InnoDB Performance Optimization Basics

Percona

Hardware Memory The amount of RAM to be provisioned for database servers can vary greatly depending on the size of the database and the specific requirements of the company. Benchmark before you decide. Typically a good value is 70%-80% of available memory. If you see concurrency issues, you can tune this variable.

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How to maximize CPU performance for PostgreSQL 12.0 benchmarks on Linux

HammerDB

HammerDB doesn’t publish competitive database benchmarks, instead we always encourage people to be better informed by running their own. So over at Phoronix some database benchmarks were published showing PostgreSQL 12 Performance With AMD EPYC 7742 vs. Intel Xeon Platinum 8280 Benchmarks .

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Crucial Redis Monitoring Metrics You Must Watch

Scalegrid

Key metrics like throughput, request latency, and memory utilization are essential for assessing Redis health, with tools like the MONITOR command and Redis-benchmark for latency and throughput analysis and MEMORY USAGE/STATS commands for evaluating memory. In addition, distributed data is a key factor in high availability.

Metrics 130
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The evolution of single-core bandwidth in multicore processors

John McCalpin

I have a lot of historical data using my ReadOnly benchmark (as described in some of the earliest entries in this blog [link] A read-only access pattern removes the need to understand and explain the many complexities associated with the “streaming stores” typically used in the STREAM benchmark (e.g., Stay tuned!