Overview
Servers Tested:
Tier Configurations:
View Results
The benchmark reports are available as interactive HTML pages at:
https://percona-lab-results.github.io/2026-pgo/index.html
Performance …
[Read more]Introduction Replication performance depends on every stage in the pipeline, from the source database to transport and ultimately to commit on the replica. On the replica side, much of that performance comes down to how efficiently changes are read, scheduled, and applied under real operational pressure. In practice, that directly affects steady-state lag, backlog recovery […]
Overview Some MySQL distribution packages, such as the generic Linux build, bundle an OpenSSL dependency within the same .tar.gz archive. With the new MySQL 8.0.46, 8.4.9 and 9.7.0 releases, we are upgrading those bundled packages from using OpenSSL 3.0 to the new OpenSSL 3.5 LTS branch. Native OS packages, such as .rpm and .deb, continue […]
The following report is covering performance evaluation of the currently available OpenSSL releases when they are used by MySQL in CPU-intensive OLTP workloads. However, the main focus is on OpenSSL-3.5.5, which will be used by default in the next MySQL releases.
Read more... (19 min remaining to read)
Benchmarking MyRocks vs. InnoDB in Memory-Constrained Environments It is a well-known fact in the database world that InnoDB is incredibly fast when the entire database fits into memory. But what happens when your data grows beyond your available RAM? MyRocks, built on RocksDB, is frequently recommended as a superior choice for environments constrained by memory, […]
As databases grow, DBAs and developers often face a tough
choice:
+ Keep historical data in production tables and risk slow
queries
+ Archive it and lose fast access
With HeatWave, you don’t have to choose. You can archive old partitions, keep recent data in production, and still run lightning-fast queries across all your data.
The post Archive Smarter, Query Faster: Unlocking MySQL Performance with HeatWave first appeared on dasini.net - Diary of a MySQL expert.
Efficiently loading CSV data into your MySQL environment is a crucial step for many analytical workloads, especially when dealing with the substantial datasets common in today's data-driven world. Both MySQL Shell's parallel import utility and HeatWave's Auto Parallel Load feature offer robust and effective solutions, each catering to slightly different needs and environments.
MySQL Shell's util.importTable provides a flexible and powerful way to import data from various sources, including local disks and OCI Object Storage, into your standard MySQL tables. It's a developer-friendly tool that offers granular control over the import process.
For those leveraging the analytical power of MySQL HeatWave, the sys.heatwave_load stored procedure, particularly with its Auto Parallel Load capabilities, simplifies the often complex task of getting data into the in-memory columnar store.
The post …
[Read more]As promised, my slides from FOSDEM25 and Pre-FOSDEM MySQL Belgian Days :
And since I was asked several times about MySQL test case demonstrating glibc-malloc memory fragmentation / leaks -- here are all the details :
Read more... (4 min remaining to read)
In MySQL 8.0 we introduced a totally new design for InnoDB REDO Log management. The main difference was about implementing a lock-free solution for user threads, and use dedicated REDO threads for all background IO write work.
for more details, see an excellent and very detailed article by Pawel : https://dev.mysql.com/blog-archive/mysql-8-0-new-lock-free-scalable-wal-design/
However, over a time we also added an option to let users to switch REDO threads=OFF to enforce REDO log processing efficiency in some particular cases. Unfortunately this feature created a lot of confusions for MySQL users, and many ones interpreted this in different ways, providing different and sometimes opposite advices, etc..
My main advice will be always : test each feature yourself and within your …
[Read more]Fragmentation is a common concern in some database systems. Highly fragmented tables can affect performance and resource allocation. But reducing fragmentation often involves rebuilding the table completely. This blog post will discuss fragmentation and its impact on InnoDB.
What is fragmentation?
We say that something is fragmented when it is formed by parts that are separate or placed in a different order than the natural one. In databases, we can experiment with different types of fragmentation: