ArangoDB, the leading open source native multi-model database, today announced the GA release of ArangoDB 3.6. ArangoDB 3.6 introduces OneShard, the ability to restrict individual databases to one node in a cluster, to ArangoDB’s Enterprise offering, and also includes major performance improvements that increase query speeds up to 30x faster.
A database created with OneShard enabled is bound to a single database server node, but still replicated synchronously to additional nodes. This ensures the high-availability and fault tolerance of a cluster setup and performance similar to a single instance, as well as the possibility to run transactions with ACID guarantees. OneShard is ideal for use cases with graph traversals and JOIN-heavy queries, as well as multi-tenant applications.
“In conversations with our community, we found many of our users expressed the need for the high-availability and fault-tolerant benefits of a cluster, but they didn’t necessarily want to scale horizontally and sacrifice performance,” said Claudius Weinberger, CEO and co-founder of ArangoDB. “With the release of ArangoDB 3.6, we are pleased to offer developers a solution with OneShard, as well as a plethora of additional performance improvements.”
The additional features in ArangoDB 3.6, included in both the Community and Enterprise editions, are:
Subquery performance optimization: 30x faster query execution time
With the introduction of a new optimizer rule called splice-subqueries, subquery splicing inlines the execution of certain subqueries, yielding up to 30x faster query execution time.
Parallel execution of AQL queries: Increase cluster AQL query speed by 40%
ArangoDB 3.6 includes the ability to parallelize work in many cluster ArangoDB Query Language (AQL) queries when there are multiple database servers involved, increasing speedups of the queries by up to 40%.
Late document materialization: Accelerate SORT and LIMIT queries by 300%
With the late document materialization optimization, ArangoDB limits sorting to index data for queries that use a combination of SORT and LIMIT, reducing memory usage and better utilizing caches. In performance testing, ArangoDB saw query speedups up to 300%.
Early pruning of non-matching documents: Query improvements up to 50% faster
ArangoDB 3.6 evaluates FILTER conditions on non-index attributes the same time it does a full collection or index scan. With the scanning and filtering happening concurrently, queries that filter on non-index attributes will run faster. In testing ArangoDB saw performance improvements up to 50%.
Additional improvements that increased query speeds up to 50% include UPDATE and REPLACE query optimizations, and faster date calculation operations.
New ArangoSearch capabilities: Support for word-based auto-completion queries and dynamic search expressions
ArangoSearch, ArangoDB’s full-text search engine with ranking capabilities, now offers edge n-grams to support word-based auto-completion queries. In ArangoDB 3.6, ArangoSearch also supports expressions with array comparison operators in AQL and the ability to mark the beginning/end of the input sequence in the n-gram Analyzer. TOKENS() and PHRASE() functions also accept arrays, enabling dynamic search expressions.