Very often, database performance is affected by the inability to cache all the required data in memory. Disk IO, even when using the fastest devices, takes much more time than a memory access. With MySQL/InnoDB, the main memory cache is the InnoDB buffer pool. There are many strategies we can try to fit as […]Read more
Please join Percona’s Chief Evangelist, Colin Charles on Tuesday, June 26th, 2018, as he presents MariaDB Server 10.3 at 7:00 AM PDT (UTC-7) / 10:00 AM EDT (UTC-4).
MariaDB Server 10.3 is out. It has some interesting features around system versioned tables, Oracle compatibility, column compression, an integrated SPIDER engine, as well as MyRocks. […]
In this blog post, we’ll look at some of the facets of InnoDB page compression.
Somebody recently asked me about the best way to handle JSON data compression in MySQL. I took a quick look at InnoDB page compression and wanted to share my findings.
There is also some great material on this topic that was prepared and […]
Being schemaless is one of the key features of MongoDB. On the bright side this allows developers to easily modify the schema of their collections without waiting for the database to be ready to accept a new schema. However schemaless is not free and one of the drawbacks is write amplification. Let’s focus on […]Read more
MongoDB includes several powerful features like high availability, read scaling, and horizontal scalability in an easy-to-use, schema-free database platform. But, what if you could retain those properties, improve performance, and ensure scalability without specialized tuning just by replacing the storage stack?
SPEAKER: Jon Tobin, Lead Sales Engineer at Tokutek
DATE: Thursday, October 9th
TIME: 1pm ET
Join Jon Tobin as he […]
Getting ready for tomorrow’s MongoDB Boston conference (come say hi if you see us!), I’m spending some time thinking about a post last week by Bryce Nyeggen: The Genius and Folly of MongoDB. It hits home in a lot of ways for me and the whole TokuMX team, because it mimics exactly the impetus […]Read more
A common MongoDB tip is to create short field names to save storage space. Because MongoDB does not compress its data on disk and stores field names in each document, using longer field names leads to bigger documents which leads to more storage space usage. The downside here is developers find short field names […]Read more
In my last post, I showed what a Fractal Tree® index is at a high level. Once again, the Fractal Tree index is the data structure inside TokuMX and TokuDB, our MongoDB and MySQL products. One of its strengths is the ability to get high levels of compression on the stored data. In this […]Read more
Tokutek is known for its full-featured fast-indexing technology. MongoDB is known for its great document-based data model and ease of use. TokuMX, version 1.0, combines the best of both worlds.
So what, exactly, is TokuMX? The simplest (but incomplete) answer is that TokuMX is MongoDB with all its storage code replaced by Tokutek’s Fractal Tree […]Read more
As we continue to test our Fractal Tree Indexing with MongoDB, I’ve been updating my benchmark infrastructure so I can compare performance, correctness, and resource utilization. Sysbench has long been a standard for testing MySQL performance, so I created a version that is compatible with MongoDB. You can grab my current version of Sysbench […]Read more