RC1 ArangoDB 3.4 – What’s new?

September 6, 201800General, ReleasesTags: arangosearch, Cluster, geo, Release

For ArangoDB 3.4 we already added 100,000 lines of code, happily deleted 50,000 lines and changed over 13,000 files until today. We merged countless PRs, invested months of problem solving, hacking, testing, hacking and testing again and are super excited to share the feature complete RC1 of ArangoDB 3.4 with you today.

Download the technical preview package for your OS: RC1 3.4 Community and RC1 3.4 Enterprise.

The team implemented over 40 new features, improvements and optimizations. In this short post, we will highlight just a few of them. You can find a full list in the release notes and follow the changes in the changelog. Read more

Index types and how indexes are used in ArangoDB: Part II

March 1, 201800GeneralTags: geo, Performance, RocksDB

In the first part of this article we dived deep into what indexes are currently available in ArangoDB (3.2 and 3.3), also briefly looking at what improvements are coming with ArangoDB 3.4. Read Part I here.

In this Part II, we are going to focus on how to actually add indexes to a data model and speed up specific queries.

Adding indexes to the data model

The goal of adding an extra index to the data model is to speed up a certain query or even multiple queries.

One of the first things that should be done during development of AQL queries should be to review the output of the explain command. A query can be explained using ArangoDB’s WEB UI or from the ArangoShell. In the ArangoShell it is as simple as db._explain(query), where query is the AQL query string. To explain a query which also has bind parameters, they need to be passed separately into the command, e.g. db._explain(query, bindParameters).
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Index types and how indexes are used in ArangoDB: Part I

February 22, 201800GeneralTags: geo, Performance, RocksDB

As in other database systems, indexes can be used in ArangoDB to speed up data retrieval queries, sometimes by many orders of magnitude. Getting the indexes set up the right way is essential for good query performance, so this is an important topic that affects most ArangoDB installations.

This is Part I of how indexes are used by ArangoDB where we discuss what types of indexes are available in the database. In Part II, we will dig deeper into how to actually add indexes to a data model and speed up specific queries. Read Part II here. Read more

An Introduction to Geo Indexes and their performance characteristics: Part II

January 18, 201800GeneralTags: geo, Performance

Geo Index Implementation

This section will cover the MMFiles based geo-index. The algorithm is optimized for in-memory accesses and optimal CPU cache utilization. The main goal for our geo queries is to reject as many distant possible result points as fast as possible. Read more

An Introduction to Geo Indexes and their performance characteristics: Part I

January 4, 201801Architecture, GeneralTags: geo, Performance

Starting with the mass-market availability of smartphones and continuing with IoT devices, self-driving cars ever more data is generated with geo information attached to it. Analyzing this data in real-time requires the use of clever indexing data-structures. Geo data in ArangoDB consists of 2 or more dimensions representing (x, y) coordinates on the earth surface. Searching on a single number is essentially a solved problem, but effectively searching on multi-dimensional data can be more difficult as standard indexing techniques cannot be used.
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A geo demonstration using Foxx

September 14, 201701Foxx, how toTags: Foxx, geo

Geo data is getting more and more important for today’s applications. The growing number of location-aware services, IoT applications and other solutions using latitude and longitude ask for precise and fast processing of geo data.

Let me show you in this quick demonstration how you can use geo functions and visualize your data using Foxx and leaflet.js. Read more