ArangoDB 3.1: Scaling Solutions, Part II
It’s not that long ago since we released ArangoDB 3.0 in which we introduced our binary storage format VelocyPack, the ArangoDB Agency for a self-managing cluster and the first persistent index by implementing Facebooks RocksDB. With all that we laid the foundation for a solid ground to scale with all three data-models.
With today’s ArangoDB 3.1 release we take things a few steps further and make cluster usage of ArangoDB more performant and convenient. Get ArangoDB 3.1.
General upgrades in 3.1
- Performance boost with our new boost-ASIO server infrastructure
- Performance boost by overhauling the ArangoDB query optimizer
- Improved internal abstraction for storage-engines as a preparation for MVCC and pluggable storage-engines
- VelocyPack over HTTP: Use our binary storage format VelocyPack over HTTP
- VelocyStream: for high performance needs you can now directly stream VelocyPack. This is already implemented in our Java driver (all other drivers maintained by ArangoDB will follow soon).
ArangoDB 3.1 Enterprise: Scaling Graphs
In addition to our community version of ArangoDB 3.1 we are excited to release our first Enterprise Edition today. The Enterprise Editions of ArangoDB focuses on enterprise-scale problems and provides useful features to meet the requirements of enterprise customers. You can download a free evaluation-only version here: Download Enterprise Edition. ArangoDB Enterprise Edition also comes with the Enterprise subscription, including comprehensive support SLA.
This first ArangoDB Enterprise Edition includes three major features:
- SmartGraphs: Scale with graphs to a cluster and stay performant. With SmartGraphs you can use the “smartness” of your application layer to shard your graph efficiently to your machines and let traversals run locally
- Encryption Control: Choose your level of SSL encryption
- Auditing: Keep a detailed log of all the important things that happened in ArangoDB
ArangoDB Spark Connector: Seamless Integration
Currently we are diving deeper into the Apache Spark world. We started with an implementation of a Spark-Connector written in Scala. The connector supports loading of data from ArangoDB into Spark and vice-versa. Today we release a first prototype with an aim of including our community into the development process early to build a product that fits your needs. Your feedback is more than welcome! Read more
ArangoDB and DC/OS Webinar: Scaling Made Simple
Wednesday, October 26th
DC/OS provides ArangoDB with exactly the infrastructure it needs for implementing a modern distributed stateful service. Join this upcoming webinar to learn how DC/OS quickly and easily deploys ArangoDB to provide scaling and fault tolerance with automatic replacement of failed components. While DC/OS supplies the management of resources and hence allows multiple services to share a common infrastructure, ArangoDB provides a modern persistence layer with its multi-model, fault-tolerant datastore. Read more
Improved Java Drivers for ArangoDB 3.1 Release
The upcoming 3.1 release comes with a binary protocol – VelocyStream – to transport VelocyPack (internal storage format of ArangoDB introduced with the 3.0 release) data between ArangoDB and client applications. VelocyPack stores a superset of JSON, is more compact and has a fast attribute lookup. On the other hand, VelocyStream allows to send VelocyPack in an optimized form over the network. We think it would be the right time to update our official Java Driver to modernize it and to let it be the first to fully support VelocyStream. Read more
ArangoDB 3.1 Release Candidate 2: What’s New
We are glad to announce that the second release candidate (RC2) of ArangoDB 3.1 is publicly available. What makes this release particularly special to us is that it also includes an official release candidate of our new Enterprise Edition with a few extra add-ons up its sleeve. The upcoming ArangoDB 3.1 will be a significant release taking effort from the solid base built with ArangoDB 3.0 which introduced our binary storage format VelocyPack, the ArangoDB Agency for a self-managing cluster architecture and the first persistent index based on Facebook’s RocksDB.
RC2 of ArangoDB 3.1 is available for download and evaluation: Community Edition & Enterprise Edition. The documentation for the ArangoDB 3.1 RC 2 can be found here.
Read more
Deploy ArangoDB 3 Cluster: 2-Click Setup
Hurray! Last week finally saw the release of ArangoDB 3.0 with lots of new features and in particular various improvements for ArangoDB clusters. In this blog post, I want to talk about one aspect of this, which is deployment.
DC/OS
As of last Wednesday, deploying an ArangoDB 3.0 cluster on DC/OS has become even simpler, because the new version of our framework scheduler has been accepted to the DC/OS Universe. Therefore, deployment is literally only two clicks: Read more
Running ArangoDB 3.0.0 on DC/OS Cluster
As you surely recognized we´ve released ArangoDB 3.0 a few days ago. It comes with great cluster improvements like synchronous replication, automatic failover, easy up- and downscaling via the graphical user interface and with lots of other improvements. Furthermore, ArangoDB 3 is even better integrated with Apache Mesos and DC/OS. Read more
ArangoDB 3.0: A Solid Foundation for Scalability
After 6 months of development we are happy and excited to announce the fully production ready ArangoDB 3.0 today! Get ArangoDB 3.0 now!
We designed ArangoDB as a native multi-model DB from the first line of code. By providing three major NoSQL data models in one technology the ArangoDB team wants to fulfill its mission to simplify data work. With ArangoDB 3 we believe that our users will come more than one step closer to a dramatically simpler way to create their applications. Read more
Discover ArangoDB 3.0: New Cluster Features
The 3.0 release of ArangoDB will introduce a completely overhauled cluster and marks a major milestone on its road to “zero-maintenance” where you can keep focus on your product instead of your datacenter.
Synchronous replication
Earlier releases of ArangoDB already featured asynchronous replication. This was already a great method to do backups and allowed for failover in case of a disaster. However that was mostly a manual job and furthermore – due to its asynchronous nature – data loss could happen. Read more
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