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, Khalid Salomão notes that “Compression would be very good to reduce storage cost and improve IO performance” and Andy notes that “SSD is getting more and more common for servers. They are very fast. The problems are high costs and low capacity.” There are many …

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 system answers queries. The pain point for most users is around the speed to answer queries. And the query speed (both latency and throughput, to be exact) depend on how the data is organized. In short: Good Indexes, Fast Queries; Poor Indexes, Slow Queries.

But building indexes is hard work, or at least it has been for the last several decades, because almost all indexing is done with B-trees. That’s true of commercial databases, of MySQL, and of most NoSQL solutions that do indexing. (The ones that don’t do …

This article is the second in a series on data fabric design and introduces the transactional data service design pattern.  The previous article in this series introduced data fabrics, which are collections of off-the-shelf DBMS servers that applications can connect to like a single server.  They are implemented from data fabric design patterns, which are reusable arrangements of DBMS servers, replication, and connectivity.  With this article we begin to look at individual design patterns in detail.

Description and Responsibilities
The transactional data service is a basic building block of data fabric architectures.  A transactional data service is a DBMS server that processes transactions submitted by applications and stores data safely.  Transactional data services have the …

Extract from THE SCALE-OUT BLOG by Robert Hodges (CEO, Continuent)http://scale-out-blog.blogspot.com Data management is undergoing a revolution. Many businesses now depend on data sets that vastly exceed the capacity of DBMS servers. Applications operate 24x7 in complex cloud environments using small and relatively unreliable VMs. Managers need to act on new information from those systems in

Apache Cassandra and BigTop updates. And more

For 451 Research clients: Kx Systems aims to slipstream the ‘big data’ bandwagon to expanded kdb+ adoption bit.ly/VxkYlC

— Matt Aslett (@maslett) January 3, 2013

For 451 Research clients: IBM sheds light on ‘big data’ integration and governance the Big Blue way bit.ly/ZTAZcw By Krishna Roy

— Matt Aslett (@maslett) January 2, 2013

The Apache Software Foundation Announces Apache Cassandra v1.2 bit.ly/UFGKFN

— Matt Aslett (@maslett) January …

Well, it’s that time of the year again for top ten lists. There have been many versions showing up on the web the last few days, including Time Magazine’s “Top 10 Everything of 2012″ list, with 55 wide ranging lists!

Last year we started using Google Analytics to see what content for blogs was most popular on Tokutek.com and generated a 2011 top ten list, ending up with a few surprises.  This year saw spikes in some interesting areas as well, including flash performance, NASA and Big Data, and MongoDB.

Without further adieu, here is the top ten list for 2012:

10. Announcing TokuDB v6.1 – This release included better overall performance and brought …

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 clustered indexes. These benchmarks show the difference that rich and efficient indexing can make to your MongoDB workload.

Given the high performance of Fractal Tree Indexes, we’ve created a new benchmark to test our ability to handle indexing large …

Two cons against NoSQL data stores read like this: 1. It’s very hard to move data out from one NoSQL to some other system, even other NoSQL. There is a very hard lock in when it comes to NoSQL. If you ever have to move to another database, you have basically to re-implement a lot [...]

This webinar covers the basics of B-trees and Fractal Tree Indexes, the benchmarks we’ve run so far, and the development road map going forward.

Date: November 13th
Time: 2 PM EST / 11 AM PST
REGISTER TODAY

Topics will include:

• What is a Fractal Tree Index?
• How to Fractal Trees compare with B-Trees
• What can a Fractal Tree do for MongoDB performance
• Benchmarks + Gotchas
• What’s next

We look forward to having you join the webinar. We also hope that by sharing these results with the community we will be able to elicit people’s …

I’ll be presenting “MongoDB and Fractal Tree Indexes” at MongoDB Boston 2012 on October 24th.  My presentation covers the basics of B-trees and Fractal Tree Indexes, the benchmarks we’ve run so far, and the development road map going forward.

I’ve been to this one day conference twice now and both times came away with a better understanding of MongoDB’s capabilities, use-cases, and many questions answered via their deep technical dives.  I highly recommend current MongoDB users and anyone considering a MongoDB project attend – it appears that seats are still available.