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TokuDB Fast Update Benchmark

 | March 28, 2013 |  Posted In: Tokutek, TokuView

Last month my colleague Rich Prohaska covered the technical details of our “Fast Update” feature which we added to TokuDB in version 6.6.  The message based architecture of Fractal Tree Indexes allows us to defer certain operations while still maintaining the semantics that MySQL users require. In the case of Fast Updates, TokuDB is avoiding the read-before-write […]

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Wanted: Evaluators to Try MongoDB with Fractal Tree Indexing

 | March 20, 2013 |  Posted In: Tokutek, TokuView

We recently resumed our discussion around bringing Fractal Tree indexes to MongoDB.  This effort includes Tokutek’s interview with Jeff Kelly at Strata as well as my two recent tech blogs which describe the compression achieved on a generic MongoDB data set and performance improvements we measured using on our implementation of Sysbench for MongoDB.  I […]

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The Last Mile for Big Data – Strata Overview with Jeff Kelly of Wikibon (Part 2)

 | March 11, 2013 |  Posted In: Tokutek, TokuView

During the second half of our CUBE discussion with Wikibon analyst Jeff Kelly at this year’s Strata Conference in Santa Clara, we talked about the tipping point for Big Data. Strata veterans could see at a glance that this year’s conference was markedly different. No longer the exclusive domain of geeks and database administrators, this […]

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MongoDB + Fractal Tree Indexes = High Compression

 | February 27, 2013 |  Posted In: Tokutek, TokuView

One doesn’t have to look far to see that there is strong interest in MongoDB compression. MongoDB has an open ticket from 2009 titled “Option to Store Data Compressed” with Fix Version/s planned but not scheduled. The ticket has a lot of comments, mostly from MongoDB users explaining their use-cases for the feature. For example, […]

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NoSQL is Great, But You Still Need Indexes

 | February 20, 2013 |  Posted In: Tokutek, TokuView

I’ve said it before, and, as is the nature of these things, I’ll almost certainly say it again: your database performance is only as good as your indexes. That’s the grand thesis, so what does that mean? In any DB system — SQL, NoSQL, NewSQL, PostSQL, … — data gets ingested and organized. And the […]

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Fast Updates with TokuDB

 | February 12, 2013 |  Posted In: Tokutek, TokuView

With TokuDB v6.6 out now, I’m excited to present one of my favorite enhancements: fast updates with TokuDB. Update intensive applications can have their throughput limited by the random read capacity of the storage system. The cause of the throughput limit is the read-modify-write algorithm that MySQL uses when processing update statements. MySQL reads a […]

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Concurrency Improvements in TokuDB v6.6 (Part 2)

 | February 5, 2013 |  Posted In: Tokutek, TokuView

In Part 1, we showed performance results of some of the work that’s gone in to TokuDB v6.6. In this post, we’ll take a closer look at how this happened, on the engineering side, and how to think about the performance characteristics in the new version. Background It’s easiest to think about our concurrency changes […]

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Concurrency Improvements in TokuDB v6.6 (Part 1)

 | January 28, 2013 |  Posted In: Tokutek, TokuView

With TokuDB v6.6 out now, I’m excited to present one of my favorite enhancements: concurrency within a single index. Previously, while there could be many SQL transactions in-flight at any given moment, operations inside a single index were fairly serialized. We’ve been working on concurrency for a few versions, and things have been getting a […]

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Tracking 5.3 Billion Mutations: Using MySQL for Genomic Big Data

 | January 22, 2013 |  Posted In: Tokutek, TokuView

University of Montreal Tracks Genomic Data With Tokutek’s TokuDB. Faster insertion rates, improved scalability and agility support lab’s fast growing research database as it grows from 100s of GBs to 1 TB and beyond. Issue addressed: MySQL database used for genomic research must be able to quickly ingest huge amounts of incoming data – hundreds […]

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