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Search Results for: performance comparison

Cache Performance Comparison

Jay Pipes continues cache experiements and has compared performance of MySQL Query Cache and File Cache. Jay uses Apache Benchmark to compare full full stack, cached or not which is realistic but could draw missleading …

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Semi-Sync replication performance in MySQL 5.7.4 DMR

I was interested to hear about semi-sync replication improvements in MySQL’s 5.7.4 DMR release and decided to check it out.  I previously blogged about poor semi-sync performance and was pretty disappointed from semi-sync’s performance across …

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A technical WebScaleSQL review and comparison with Percona Server

The recent WebScaleSQL announcement has made quite a splash in the MySQL community over the last few weeks, and with a good reason. The collaboration between the major MySQL-at-scale users to develop a single code …

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LVM read performance during snapshots

For the same customer I am exploring ZFS for backups, the twin server is using regular LVM and XFS. On this twin, I have setup mylvmbackup for a more conservative backup approach. I quickly found …

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Sysbench Benchmark for MongoDB – v0.1.0 Performance Update

Two months ago I posted a performance comparison running Sysbench on MongoDB versus MongoDB with Fractal Tree Indexes v0.0.2. The benchmark showed a 133% improvement in throughput. Nice, but our engineering team had an effort …

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532x Multikey Index Insertion Performance Increase for MongoDB with Fractal Tree Indexes

In my three previous MongoDB blogs I wrote about our implementation of Fractal Tree(R) indexes on MongoDB, showing a 10x insertion performance increase, a 268x query performance increase, and a comparison of covered indexes and …

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268x Query Performance Increase for MongoDB with Fractal Tree Indexes, SAY WHAT?

Last week I wrote about our 10x insertion performance increase with MongoDB. We’ve continued our experimental integration of Fractal Tree® Indexes into MongoDB, adding support for clustered indexes.  A clustered index stores all non-index fields …

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Impact of memory allocators on MySQL performance

MySQL server intensively uses dynamic memory allocation so a good choice of memory allocator is quite important for the proper utilization of CPU/RAM resources. Efficient memory allocator should help to improve scalability, increase throughput and …

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Write Optimization: Myths, Comparison, Clarifications, Part 2

In my last post, we talked about the read/write tradeoff of indexing data structures, and some ways that people augment B-trees in order to get better write performance. We also talked about the significant drawbacks …

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Write Optimization: Myths, Comparison, Clarifications

Some indexing structures are write optimized in that they are better than B-trees at ingesting data. Other indexing structures are read optimized in that they are better than B-trees at query time. Even within B-trees, …

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