Roadmap

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Roadmap

ArangoDB 3.2 - released on July 20th 2017

RocksDB & Pluggable Storage Engine
Additional storage engine for ArangoDB to work with huge datasets. Document level locking on writes, no locking on reads

Distributed Graph Processing with Pregel
Use incremental graph processing algorithms in a single mode server or cluster

Fault-Tolerant Foxx
Foxx service are now self-healing, even if all coordinators go down.

Geo_Cursor
Get documents sorted by distance to a certain point in space. You can also apply filters and limits to geo_cursor. E.g. “Give me 10 vegetarian restaurants within a 1 mile radius to X”

Arangoexport

Export your data in multiple formats. Export graphs data to xgmml format for Cytoscape visualizations or arbitrary collections to JSON or JSONL

Satellite Collections (Enterprise Edition)
Satellite Collections enable faster join operations when working with sharded datasets and avoid expensive network hops during join processing among machines.

Encryption at Rest (Enterprise Edition)
Even if a disk gets stolen, data can’t be accessed.

LDAP (Enterprise Edition)
ArangoDB can now be integrated with LDAP allowing for an external authentication server to manage users.

ArangoDB 3.1 - Released November 3rd 2016

VelocyPack over HTTP
Stream binary storage VelocyPack over HTTP

VelocyStream
Directly stream our binary format VelocyPack for high performance needs

boost-ASIO server infrastructure
Performance boost with new boost-ASIO

Stand-Alone Agency
Use ArangoDB as a resilient, RAFT-based key/value store as alternative to ZooKeeper or etcd

AQL Editor
Much easier to use. Choose JSON, tabular or graph outputs. Simplified elaboration of queries with new Query Performance Profiler

New Graph Viewer
Suitable for large graph visualization with much more features. First WebGL implementation

Overhauled Query Optimizer
Better overall query execution and performance increases

Preparations for pluggable storage engine and MVCC
Improved abstraction to integrate pluggable storage engine and MVCC

Vertex-Centric Indices
Generate indices on edges which are a combination of vertex and attribute

New Java Driver
Multi-document operations, VelocyStream ready, asynchronous request handling

SmartGraphs (Enterprise Edition)
Shard large graph datasets to a cluster and stay close to the performance of a single instance

Auditing (Enterprise Edition)
Keep a detailed log of all the important things that happened in ArangoDB

Encryption Control (Enterprise Edition)
Choose your level of SSL encryption

Future Plans For ArangoDB 3.x Development Cycle

Automatic Rebalance
It will be possible to utilize storage among multiple machines automatically.

Lock-free Cursors
Removing as many locks as possible will allow for even better parallelism of queries.

Improved Indexes (array, text, geo)
We plan to add or improve the existing indexes or add new features.

Zero Administration
Reduces the administration cost as much as possible.

General Geo Functions
General geo functions help you deal with arbitrary polygons.

HTTP 2.0 and/or WebSockets
Support for new Web-protocols like HTTP 2.0 or WebSockets.

Collection Level Security
It will be possible to assign different authorization levels to various collections.

Vertex-centric Indexes
Vertex-centric indexes allow you to handle near neighbors very fast.

Data Compression
Allow to compress big text fields to trade time for memory.

Constraints
Define constrains on your collection, in order to validate data entered.

Trigger
Trigger a Javascript function as soon as a modification occurs.

Binary Data
Support for big data blobs.

Distributed Transaction
Transactions in a distributed environment with a transaction manager.

Range Sharding
Instead of sharding based on a hash value, allow to shard ranges.

ArangoDB 3.0 - Released June 23th 2016

VelocyPack
Internal storage will change from JSON to VelocyPack for enhanced performance, smaller footprint and binary support.

Persistent Indexes
We plan on making indexes persistent, which will allow using quicker recovery, start-up and larger datasets.

Low-Level C++ Driver
Implementation of efficient, reusable, platform-independent core driver functionality to be used in multiple client languages.

Auto-failover
Allow for automatic failover to slave nodes. A monitor process detects network failures and automatically switches to backup nodes.

Master/Master Replication
Replicate data not just in a master/slave fashion, but also as true master/master.

Automatic Failover with Mesos
This release will contain the next iteration of our Mesosphere DCOS integration and will thus offer convenient set-up of synchronous replication and full automatic failover.

Health Check Dashboard in Mesos
Enables you to see the health status of your ArangoDB cluster in Mesos dashboard.

Cluster Dashboard
Improved cluster administration will be implemented.

Distributed Failover
Instead of dedicated slave, you can use spare capacity on masters to hold the slave for other shards.

Past releases

ArangoDB 2.8 – released 25/01/2016 ✓

Array Indexes
Hash indexes and skiplist indexes support array values so they index individual array members.

Graph Traversals in AQL
Using AQL to traverse a graph / edge collections.

AQL Optimization
Reimplemented AQL functions in C++ for improved performance.

New Framework in Mesosphere DCOS 1.3
ArangoDB package for DCOS 1.3, enhanced replication and failover.

Automatic Deadlock Detection for Transactions
The new deadlock detection mechanism will kick in automatically when it detects operations that are mutually waiting for each other.

ArangoDB 2.7 - released 09/10/2015 ✓

Replication Improvements
This allows much easier synchronization of a single collection from a master to a slave server.

Throughput Enhancements
A lot is not enough. Throughput is another key requirement for a premium database. Again we pushed our throughput a big step forward with 2.7.

Improved Date Handling in AQL
AQL functions for date and time calculation and manipulation.

Index Buckets
Split primary indexes and hash indexes into multiple index buckets.

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