Highlights

    • ArangoSearch: Wildcard and fuzzy search ( and n-gram based), enhanced , improved late document materialization and Views covering queries using their indexes without touching the storage engine, as well as a new SIMD-based index format for faster processing and for 15 additional languages.

    • Schema Validation: Enforce a JSON Schema for documents on collection level. Invalid documents can be rejected automatically by the database system, making it easy to maintain data quality.

    • : New document API operations to upsert documents and to efficiently insert documents while skipping the creation if the document exists already.

    • AQL: Improved subquery and , among many optimizations and enhancements.

    • HTTP/2 support: Better load-balancer and Kubernetes compatibility, improved request throughput.

    Enterprise Edition

    • : Synchronously replicated graphs with local traversal execution.

    • Disjoint SmartGraphs: Improve traversal execution times for SmartGraphs without edges between vertices with different SmartGraph attributes.

    • : Optional parallel execution of nested traversals for single servers and OneShard clusters.

    • Security: Added support for multiple JWT Secrets and the ability to hot-reload them from disk, , Encryption at rest key rotation and .

    Also see What’s New in 3.7.

    Version 3.6

    All Editions

    • ArangoSearch: New Analyzer options for edge n-grams (text Analyzer), UTF-8 encoded n-gram input and optional start/end markers (ngram Analyzer). Support for using arrays (array comparison operators in queries and the TOKENS() / PHRASE() functions accept arrays). Views can benefit from the SmartJoins optimization.

    Enterprise Edition

    • OneShard deployments offer a practicable solution that enables significant performance improvements by massively reducing cluster-internal communication. A database created with OneShard enabled is limited to a single DB-Server node but still replicated synchronously to ensure resilience. This configuration allows running transactions with ACID guarantees on shard leaders.

    Also see .

    All Editions

    • ArangoSearch: The search and ranking engine received an upgrade and now features Configurable Analyzers, and several improvements to the AQL integration.

    • AQL Graph Traversals: allows you to query not just for one shortest path between two documents but multiple, sorted by length or weight. With PRUNE you can stop walking down certain paths early in a graph traversal to improve its efficiency.

    • : Perform multi-document transactions with individual begin and commit / abort commands using the new HTTP endpoints or via a supported driver.

    • Time-to-Live : TTL indexes can be used to automatically remove documents in collections for use cases like expiring sessions or automatic purging of statistics or logs.

    • Data Masking: arangodump provides a convenient way to extract production data but mask critical information that should not be visible.

    Enterprise Edition

    • : Create automatic, consistent backups of your cluster without noticeable impact on your production systems. In contrast to arangodump, hot backups are taken on the level of the underlying storage engine and hence both backup and restore are considerably faster.

    • SmartJoins: Run joins between identically sharded collections with performance close to that of a local join operation.

    • Advanced Data Masking: There are additional available in the Enterprise Edition, such as for substituting email addresses and phone numbers with similar looking pseudo-data.

    Also see What’s New in 3.5.

    Version 3.4

    All Editions

    • ArangoSearch: Search and similarity ranking engine integrated natively into ArangoDB and AQL. ArangoSearch combines Boolean retrieval capabilities with generalized ranking algorithms (BM25, TFDIF). Support of e.g. relevance-based searching, phrase and prefix-matching, complex boolean searches and query time relevance tuning. Search can be combined with all supported data models in a single query. Many specialized language Analyzers are already included for e.g. English, German, French, Chinese, Spanish and many other language.

    • and S2 Geo Index: ArangoDB now supports all geo primitives. (Multi-)Point, (Multi-)LineStrings, (Multi-)Polygons or intersections can be defined and queried for. The Google S2 geo index is optimized for RocksDB and enables efficient querying. Geo query results are automatically visualized with an OpenStreetMap integration within the Query Editor of the web interface.

    • : Enables the analysis of queries and adds additional information for the user to identify optimization potentials more easily. The profiler can be accessed via Arangosh with db._profileQuery(...) or via the Profile button in the Query Editor of the web interface.

    • Streaming Cursors: Cursors requested with the stream option on make queries calculate results on the fly and make them available for the client in a streaming fashion, as soon as possible.

    • RocksDB as Default Storage Engine: With ArangoDB 3.4 the default for fresh installations will switch from MMFiles to RocksDB. Many optimizations have been made to RocksDB since the first release in 3.2. For 3.4 we optimized the binary storage format for improved insertion, implemented “optional caching”, reduced the replication catch-up time and much more.

    Also see What’s New in 3.4.

    Enterprise Edition

    • : Replicate the entire structure and content of an ArangoDB cluster asynchronously to another cluster in a different datacenter with ArangoSync. Multi-datacenter support means you can fallback to a replica of your cluster in case of a disaster in one datacenter.

    All Editions

    • Server-level Replication: In addition to per-database replication, there is now an additional globalApplier. Start the global replication on the slave once and all current and future databases will be replicated from the master to the slave automatically.

    • : Make a single server instance resilient with a second server instance, one as master and the other as asynchronously replicating slave, with automatic failover to the slave if the master goes down.

    Also see What’s New in 3.3.

    Version 3.2

    All Editions

    • Pregel: We implemented distributed graph processing with Pregel to discover hidden patterns, identify communities and perform in-depth analytics of large graph data sets.

    • : The Foxx management internals have been rewritten from the ground up to make sure multi-coordinator cluster setups always keep their services in sync and new Coordinators are fully initialized even when all existing Coordinators are unavailable.

    Enterprise Edition

    • LDAP integration: Users and permissions can be managed from outside ArangoDB with an LDAP server in different authentication configurations.

    • : Let the server persist your sensitive data strongly encrypted to protect it even if the physical storage medium gets stolen.

    • SatelliteCollections: Faster join operations when working with sharded datasets by synchronously replicating selected collections to all DB-Servers in a cluster, so that joins can be executed locally.

    Also see .

    All Editions

    • Vertex-centric indices: AQL traversal queries can utilize secondary edge collection indexes for better performance against graphs with supernodes.

    • : In addition to JSON, the binary storage format VelocyPack can now also be used in transport over the HTTP protocol, as well as streamed using the new bi-directional asynchronous binary protocol VelocyStream.

    Enterprise Edition

    • 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

    • Auditing: Keep a detailed log of all the important things that happened in ArangoDB.

    Also see .

    Version 3.0

    • with synchronous replication, master/master setup, shared nothing architecture, cluster management Agency.

    • Deeply integrated, native AQL graph traversal

    • as new internal binary storage format as well as for intermediate AQL values.

    • Persistent indexes via RocksDB suitable for sorting and range queries.

    • Significantly improved