To investigate the impact of the Meltdown and Spectre patches on the performance of ArangoDB, we ran benchmark tests with the two storage engines available in ArangoDB (MMFiles & RocksDB). We used the arangobench benchmark and test tool for these tests.
The tests include 10 different test cases with changing test parameters like concurrency, batch requests and asynchronous execution. Read more
I have varying levels of familiarity with Google’s original leveldb and three of its derivatives. RocksDB is one of the three. In each of the four leveldb offerings, the code is optimized for a given environment. Google’s leveldb is optimized for a cell phone, which has much more limited resources than a server. RocksDB is optimized for flash arrays on a large servers (per various Rocksdb wiki pages). Note that a flash array is a device of much higher throughput than a SATA or SSD drive or array. It is a device that sits on the processor’s bus. RocksDB’s performance benchmark page details a server with 24 logical CPU cores, 144GB ram, and two FusionIO flash PCI devices. Each FusionIO device cost about $10,000 at the time of the post. So RocksDB is naturally tuned for extremely fast and expensive systems. Here is an example Arangodb import on a machine similar to the RocksDB performance tester: Read more
We are pleased to announce the release of ArangoDB 3.2. Get it here. After an unusually long hackathon, we eliminated two large roadblocks, added a long overdue feature and integrated an interesting new one into this release. Furthermore, we’re proud to report that we increased performance of ArangoDB on average by 35%, while at the same time reduced the memory footprint compared to version 3.1. In combination with a greatly improved cluster management, we think ArangoDB 3.2 is by far our best work. (see release notes for more details)
One key goal of ArangoDB has always been to provide a rock solid platform for building ideas. Our users should always feel safe to try new things with minimal effort by relying on ArangoDB. Todays 3.2 release is an important milestone towards this goal. We’re excited to release such an outstanding product today. Read more
We’re excited to release today the beta of ArangoDB 3.2. It’s feature rich, well tested and hopefully plenty of fun for all of you. Keen to take it for a spin? Get ArangoDB 3.2 beta here.
With ArangoDB 3.2, we’re introducing the long-awaited pluggable storage engine and its first new citizen, RocksDB from Facebook
The goal of the whole ArangoDB 3 release cycle has been to scale the multi-model idea to new heights. Getting ‘ready’ for large scale applications is not done overnight and it’s definitely not possible without the help of a strong community. We’d like to invite all of you to lend us a helping hand to make ArangoDB 3.2 the best release ever. Please push this beta to its limits: test it for your use cases and compare the performance of the new features like RocksDB. Let us know on Github any bug that you find. Don’t worry about hurting our feelings: we want to fix any problems.
Join the Beta Bug Hunt Challenge and win a $200 Amazon Gift Card as first prize. You can find more details about this reward program at the end of this post. Read more
The new release of ArangoDB 3.2 is just around the corner and will include some major improvements like distributed graph processing with Pregel or a powerful export tool. But most importantly we integrated Facebook’s RocksDB as the first pluggable storage engine in ArangoDB. With RocksDB you will be able to use as much data in ArangoDB as fits on your disc.
As this is an important change and many questions reached us from the community we wanted to share some answers on the most common questions. Please find them below
Will I be able to go beyond the limit of RAM?
Yes. By defining RocksDB as your storage engine you will be able to work with as much data as fits on your disc.
What is the locking behaviour with RocksDB in ArangoDB?
