Jan Steemann, Author at ArangoDB - Page 2 of 11

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

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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

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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

Present and Future of ArangoDB Fulltext Index

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The ArangoDB Fulltext index allows you to search for text in arbitrary strings. It is a great way to implement things like autocompletion, product searches or many other use-cases which need some form of fulltext search.
The Fulltext Index is suitable for you if your use-case can be broken down to:
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An Introduction to Geo Indexes and their performance characteristics: Part I

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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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Introduction to Fuerte – The ArangoDB C++ Driver

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In this post, we will introduce you to our new ArangoDB C++ diver fuerte. fuerte allows you to communicate via HTTP and VST with ArangoDB instances. You will learn how to create collections, insert documents, retrieve documents, write AQL Queries and how to use the asynchronous API of the driver.

Requirements (Running the sample)

Please download and inspect the sample described in this post. The sample consists of a C++ – Example Source Code – File and a CMakeLists.txt. You need to install the fuerte diver, which can be found on github, into your system before compiling the sample. Please follow the instructions provided in the drivers README.md. Read More

Milestone 2 ArangoDB 3.3 – New Data Replication Engine and Hot Standby

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We’re pleased to announce the availability of the Milestone 2 of ArangoDB 3.3. There are a number of improvements, please consult the changelog for a complete overview of changes.

This milestone release contains our new and improved data replication engine. The replication engine is at the core of every distributed ArangoDB setup: whether it is a typical master/slave setup between multiple single servers or a full-fledged cluster. During the last month we:

  • redesigned the replication protocol to be more reliable
  • refactored and modernized the internal infrastructure to better support continuous asynchronous replication
  • added a new global asynchronous replication API, to allow you to automatically and continuously mirror an entire ArangoDB single-instance (master) onto another one (or more)
  • added support for automatic failover from a master server to one of his replica-slaves, if the master server becomes unreachable

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Alpha3 of ArangoDB 3.2: Support for Distributed Graph Processing

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The next alpha release of the upcoming ArangoDB 3.2 is available for testing. You can download and install alpha3 here.

Moving forward

As ArangoDB 3.2 will include several new features and improvements, we realized that the release model that we currently follow has room for improvement. Going forward we will introduce milestone releases with ArangoDB 3.3. For this major release you will see a bit more alphas. You can read detailed info about the new structure model here.

Pregel computing model

In this alpha we introduce support for incremental graph processing algorithms in a single mode server as well as in the cluster. Read more