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Displaying posts with tag: MariaDB ColumnStore (reset)
MariaDB Track at Percona Live

Less than one month left until Percona Live. This time the Committee work was a bit unusual. Instead of having one big committee for the whole conference we had a few mini-committees, each responsible for a track. Each independent mini-committee, in turn, had a leader who was responsible for the whole process. I led the MariaDB track. In this post, I want to explain how we worked, which topics we have chosen, and why.

For MariaDB, we had seven slots: five for 50-minutes talks, two for 25-minutes talks and 19 submissions. We had to reject two out of three proposals. We also had to decide how many topics the program should cover. My aim here was to use the MariaDB track to demonstrate as many MariaDB unique features as …

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This Week in Data with Colin Charles #54: Percona Server for MySQL is Alpha

Join Percona Chief Evangelist Colin Charles as he covers happenings, gives pointers and provides musings on the open source database community.

I consider this to be the biggest news for the week: Alpha Build of Percona Server for MySQL 8.0. Experiment with it in a Docker container. It is missing column compression with dictionary support, native partitioning for TokuDB and MyRocks (excited to see that this is coming!), and encryption key rotation and scrubbing. All in, this should be a fun release to try, test, and also to file bugs for!

Database paradigms are changing, and it is interesting to see Cloudflare introducing Workers KV a key-value store, that is eventually consistent and highly distributed (at their global …

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Column Store Database Benchmarks: MariaDB ColumnStore vs. Clickhouse vs. Apache Spark

This blog shares some column store database benchmark results, and compares the query performance of MariaDB ColumnStore v. 1.0.7 (based on InfiniDB), Clickhouse and Apache Spark.

I’ve already written about ClickHouse (Column Store database).

The purpose of the benchmark is to see how these three solutions work on a single big server, with many CPU cores and large amounts of RAM. Both systems are massively parallel (MPP) database systems, so they should use many cores for SELECT queries.

For the benchmarks, I chose …

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