Do Graph Databases Scale? Yes? No? Let’s see!

00cluster, General, Graphs, Performance

Graph Databases are a great solution for many modern use cases: Fraud Detection, Knowledge Graphs, Asset Management, Recommendation Engines, IoT, Permission Management … you name it. 

All such projects benefit from a database technology capable of analyzing highly connected data points and their relations fast – Graph databases are designed for these tasks.

But the nature of graph data poses challenges when it comes to *buzzword alert* scalability. So why is this, and are graph databases capable of scaling? Let’s see…

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AWS Neptune: A New Vertex in the Graph World — But Where’s the Edge?

14cluster, General, Graphs, Performance

At AWS Re:Invent just a few days ago, Andy Jassy, the CEO of AWS, unveiled their newest database product offerings: AWS Neptune. It’s a fully managed, graph database which is capable of storing RDF and property graphs. It allows developers access to data via SPARQL or java-based TinkerPop Gremlin. As versatile and as good as this may sound, one has to wonder if another graph database will solve a key problem in modern application development and give Amazon an edge over its competition. Read More

AQL optimizer improvements for 2.8

00PerformanceTags: , ,

With the 2.8 beta phase coming to an end it’s time to shed some light on the improvements in the 2.8 AQL optimizer. This blog post summarizes a few of them, focusing on the query optimizer. There’ll be a follow-up post that will explain dedicated new AQL features soon. Read more

AQL Function Speedups in 2.8

00PerformanceTags: , ,

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: Read more

Using Multiple Indexes Per Collection

03Documentation, PerformanceTags: ,

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. Read more

Index Speedups in 2.8

01PerformanceTags: , ,

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. Read more