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Alpha 1 of the upcoming ArangoDB 3.7
We released ArangoDB version 3.6 in January this year, and now we are already 6 weeks into the development of its follow-up version, ArangoDB 3.7. We feel that this is a good point in time to share some of the new features of that upcoming release with you! We try not to develop new features…
Neo4j Fabric: Scaling out is not only distributing data
Neo4j, Inc. is the well-known vendor of the Neo4j Graph Database, which solely supports the property graph model with graphs of previously limited size (single server, replicated). In early 2020, Neo4j finally released its 4.0 version which promises “unlimited scalability” by the new feature Neo4j Fabric. While the marketing claim of “scalability” is true seen…
ArangoML Pipeline Cloud – Managed Machine Learning Metadata Service
We all know how crucial training data for data scientists is to build quality machine learning models. But when productionizing Machine Learning, Metadata is equally important. Consider for example: Capture of Lineage Information (e.g., Which dataset influences which Model?) Capture of Audit Information (e.g, A given model was trained two months ago with the following…
Efficient Massive Inserts into ArangoDB with Node.js
Nothing performs faster than arangoimport and arangorestore for bulk loading or massive inserts into ArangoDB. However, if you need to do additional processing on each row inserted, this blog will help with that type of functionality. If the data source is a streaming solution (such as Kafka, Spark, Flink, etc), where there is a need…
What’s new in ArangoDB 3.6: OneShard Deployments and Performance Improvements
Welcome 2020! To kick off this new year, we are pleased to announce the next version of our native multi-model database. So here is ArangoDB 3.6, a release that focuses heavily on improving overall performance and adds a powerful new feature that combines the performance characteristics of a single server with the fault tolerance of…
Release Candidate 2 of the ArangoDB 3.6 available for testing
We are working on the release of ArangoDB 3.6 and today, just in time for the holiday season, we reached the milestone of RC2. You can download and take the RC2 for a spin: Community Edition and Enterprise Edition.
ArangoDB and the Cloud-Native Ecosystem: Integration Insights
ArangoDB is joining CNCF to continue its focus on providing a scalable native multi-model database, supporting Graph, Document, and Key-Value data models in the Cloud Native ecosystem. ArangoDB ArangoDB is a scalable multi-model model database. What does that mean? You might have already encountered different NoSQL databases specialized for different data models e.g., graph or…
Say Hi To ArangoDB ArangoGraph: A Fully-Managed Multi-Model Database Service
After two years of planning, preparation and a few lines of code, you can now enjoy an even more comfortable developers’ life with ArangoDB. Today, we are happy to announce the launch of ArangoDB’s managed service ArangoGraph– a fully-managed graph database, document, and key-value store, as well as a full-text search engine – in one…
Building Our Managed Service on Kubernetes: ArangoDB Insights
Running distributed databases on-prem or in the cloud is always a challenge. Over the past years, we have invested a lot to make cluster deployments as simple as possible, both on traditional (virtual) machines (using the ArangoDB Starter) as well as on modern orchestration systems such as Kubernetes (using Kube-ArangoDB). However, as long as teams…
ArangoDB Hot Backup: Creating Consistent Cluster-Wide Snapshots
Introduction “Better to have, and not need, than to need, and not have.” Franz Kafka Franz Kafka’s talents wouldn’t have been wasted as DBA. Well, reasonable people might disagree. With this article, we are shouting out a new enterprise feature for ArangoDB: consistent online single server or cluster-wide “hot backups.”
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