Building a Mini Database Cluster for Fun – LEGO Edition

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Mini PC Database Cluster for Fun Lego

ArangoDB is a native multi-model database that could be deployed as a single database, in active failover mode or as a full blown database cluster in the cloud. To try things out I can even run a cluster on my local development machine.

Well, yes… but I wanted to be more real, 24×7, with the opportunity to manipulate all the things…

Inspired by other Raspberry PI & mini-cluster projects, I thought I could build my own, bare metal, desk compatible Mini PC database cluster.

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Sharding: freedom, when you need it least?

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“I must have a prodigious amount of mind;
it takes me as much as a week, sometimes, to make it up!”
― Mark Twain

How many shards should one choose, when creating collections in ArangoDB clusters?

TLDR: Don’t be too shy with sharding your data in many shards across your cluster. Be mindful however that AQL-heavy applications might not profit as much from heavy distribution. Read more

Run multiple versions of ArangoDB in parallel using the .tar.gz distribution

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This post uses the new .tar.gz binary distribution of ArangoDB to run multiple versions of ArangoDB alongside each other on the same machines. We will do a production-ready deployment on 3 cloud instances with authentication, TLS encryption, (self-signed) certificates and systemd service. In the end, we show how to perform a rolling upgrade for one of the clusters to a new version. Read more

Deploying ArangoDB 3.4 on Kubernetes

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It has been a few months since we first released the Kubernetes operator for ArangoDB and started to brag about it. Since then, quite a few things have happened.

For example, we have done a lot of testing, fixed bugs, and by now the operator is declared to be production ready for three popular public Kubernetes offerings, namely Google Kubernetes Engine (GKE), Amazon Elastic Kubernetes Service (EKS) and Pivotal Kubernetes Service (PKS) (see here for the current state of affairs). Read more

ArangoDB 3.4 GA
Full-text Search, GeoJSON, Streaming & More

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The ability to see your data from various perspectives is the idea of a multi-model database. Having the freedom to combine these perspectives into a single query is the idea behind native multi-model in ArangoDB. Extending this freedom is the main thought behind the release of ArangoDB 3.4.

We’re always excited to put a new version of ArangoDB out there, but this time it’s something special. This new release includes two huge features: a C++ based full-text search and ranking engine called ArangoSearch; and largely extended capabilities for geospatial queries by integrating Google™ S2 Geometry Library and GeoJSON.  Read more

RC1 ArangoDB 3.4 – What’s new?

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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. Read more

The ArangoDB Operator for Kubernetes – Stateful Cluster Deployments in 5min

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At ArangoDB we’ve got many requests for running our database on Kubernetes. This makes complete sense since Kubernetes is a highly popular system for deploying, scaling and managing containerized applications.

Running any stateful application on Kubernetes is a bit more involved than running a stateless application, because of the storage requirements and potentially other requirements such as static network addresses. Running a database on Kubernetes combines all the challenges of running a stateful application, combined with a quest for optimal performance.

This article explains what is needed to run ArangoDB on Kubernetes and what we’re doing to make it a lot easier. Read more

ArangoDB Cluster Administration Course Released

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Cluster Administration course will take you all the way from concept and anatomy of the ArangoDB cluster to maintenance, resilience and troubleshooting of your distributed environment.

When data size or workload makes purchasing of a single database server prohibitive one needs to rethink the system architecture and consider to cluster a farm of more affordable machines. While ArangoDB clusters bring additional added value like seamless runtime scaling and thin provisioning, their management can look testy and challenging. Read more

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