While working on the upcoming ArangoDB 2.8, we have reimplemented some AQL functions in C++ for improved performance. AQL queries using these functions may benefit from using the new implementation of the function.

The following list shows the AQL functions for which a C++ implementation has been added in 2.8. The other C++-based AQL function implementations added since ArangoDB 2.5 are also still available. Here’s the list of functions added in 2.8:

• document-related functions: DOCUMENT, EDGES, PARSE_IDENTIFIER
• numerical functions: ABS, FLOOR, RAND, ROUND, SQRT
• statistical functions:..

The query optimizer in ArangoDB 2.8 has been improved in terms of how it can make use of indexes. In previous versions of ArangoDB, the query optimizer could use only one index per collection used in an AQL query. When using a logical OR in a FILTER condition, the optimizer did not use any index for the collection in order to ensure the result is still correct.

This is much better in 2.8. Now the query optimizer can use multiple indexes on the same collection for FILTER conditions that are combined with a logical OR.

For all following queries, I have set up a collection named test, which has..

The upcoming 2.8 version of ArangoDB will provide several improvements in the area of index usage and query optimization.

First of all, hash and skiplist indexes can now index individual array values. A dedicated post on this will follow shortly. Second, the query optimizer can make use multiple indexes per collection for queries with OR-combined filter conditions. This again is a subject for another post. Third, there have been some speed improvements due to changes in the general index handling code. This is what this post is about.

In order to assess the speedups in 2.8, I have run some..

The AQL editor in the web interface is useful for running ad hoc AQL queries and trying things out. It provides a feature to explain the query and inspect its execution plan. This can be used to check if the query uses indexes, and which.

So far the AQL editor only supported using query string literals, but it lacked support for bind parameters. Queries issued by application code however often will use bind parameters for security reasons. Often enough this prevented copying & pasting queries from the application code into the AQL editor and vice versa without making manual adjustments.

Long awaited and now we´ve finished it! New major release of ArangoDB 2.7 is ready for download. First of all a big thanks to our community for your great support! We´ve implemented a lot of your ideas! After your feedback to RC1 and RC2 we are happy to bring a new major release to the world. With ArangoDB 2.7 we increased our performance even further and improved query handling a lot.

What big improvements are in for you?

Index buckets

I recently wrote two recipes about generating AQL query strings. They are contained in the ArangoDB cookbook by now:

• Avoiding parameter injection in AQL
• Writing multi-line AQL queries

After that, Github user tracker1 suggested in Github issue 1457 to take the ES6 template string variant even further, using a generator function for string building, and also using promises and ES7 async/await.

We can’t use ES7 async/await in ArangoDB at the moment due to lacking support in V8, but the suggested template string generator function seemed to be an obvious improvement that deserved inclusion in..

ArangoDB’s devel branch recently saw a change that makes writing some AQL queries a bit simpler.

The change introduces an optional shorthand notation for object attributes in the style of ES6’s enhanced object literal notation.

Last week saw the addition of the RETURN DISTINCT for AQL queries. This is a new shortcut syntax for making result sets unique.

For this purpose it can be used as an easier-to-memorize alternative for the already existing COLLECT statement. COLLECT is very flexible and can be used for multiple purposes, but it is syntactic overkill for making a result-set unique.

For the ArangoDB 2.6 release from last week we’ve put some performance tests together. The tests will compare the AQL query execution times in 2.5 and 2.6.

The results look quite promising: 2.6 outperformed 2.5 for all tested queries, mostly by factors of 2 to 5. A few dedicated AQL features in the tests got boosted even more, resulting in query execution time reductions of 90 % and more. Finally, the tests also revealed a dedicated case for which 2.6 provides a several hundredfold speedup.

Also good news is that not a single of the test queries ran slower in 2.6 than in 2.5.

With ArangoDB 2.6 being in beta already, it’s time to look at some features scheduled for 2.7. Today I’ll showcase a few AQL parser improvements that are present in the devel branch already, which will be the foundation for the 2.7 release.

Star operator

The already existing star operator ([*]) is much more flexible in 2.7 than in previous ArangoDB versions. It now allows filtering the values it iterates over, and optional projections.

These features will be demonstrated using the following example member data:

[ { "name" : "sir alfred", "age" : 60, "likes" : [ "lettuce", "tortoises" ] }, {..