CAVEAT: This post deals with a development version of MongoDB and represents very early testing. The version used was not even a release candidate – 2.7.9-pre to be specific, this is not even a release candidate.  Therefore any and all details may change significantly before the release of 2.8, so please be aware that nothing is yet finalized and as always, read the release notes once 2.8.0 ships.

Update (Nov 17th, 2014): Good news! I have re-tested with a patched version of 2.8.0-rc0 and the results are very encouraging compared to figure 2 below.  For full details (including an updated graph), see MongoDB 2.8: Improving WiredTiger Performance

Anyone that follows the keynotes from recent MongoDB events will know that we have demonstrated the concurrency performance improvements coming in version 2.8 several times now.  This is certainly the headline performance improvement for MongoDB 2.8, with concurrency constraints in prior versions leading to complex database/collection layouts, complex deployments and more to work around the per-database locking limitations.

However, the introduction of the new WiredTiger storage engine that was announced at MongoDB London also adds another capability with a performance component that has long been requested: compression

Eliot also gave a talk about the new storage engines at MongoDB London last week after announcing the availability of WiredTiger in the keynote.  Prior to that we were talking about what would be a good way to structure that talk and I suggested showing the effects and benefits of compression. Unfortunately there wasn’t enough time to put something meaningful together on the day, but the idea stuck with me and I have put that information together for this blog post instead.

It’s not a short post, and it has graphs, so I’ve put the rest after the jump.