jarrest.blogg.se - Arangodb performance

ARANGODB PERFORMANCE FULL
ARANGODB PERFORMANCE SERIES
ARANGODB PERFORMANCE FREE

Cluster support with synchronous replication and automatic failover.Improved query editor and query explain output.Low-latency request handling using a boost-ASIO server infrastructure.New viewer for large graphs, supporting WebGL.Support for vertex-centric indexes for more efficient graph traversals with filter conditions.Value-based sharding of large graph datasets for better data locality when traversing graphs ("SmartGraphs").Support for composable, distance-based geo-queries.

Collections replicated on all cluster nodes to execute joins with sharded data locally ("SatelliteCollections").Distributed iterative graph processing with Pregel in single server and cluster.Deployment mode for single servers with automatic failover.Datacenter to Datacenter Replication for disaster recovery ("DC2DC").Multi-threaded dump and restore operations.Native implementations in C++ of all built-in query functions.Cluster-distributed aggregation queries.Query profiling to show detailed runtime information.Round-robin load-balancer support for cloud environments.Insert operations can be turned into a replace automatically, in case that the target document already exists ("Repsert").Improved geo-spatial index with GeoJSON support.Integrated full-text search and information retrieval engine ("ArangoSearch").Data masking capabilities for attributes containing sensitive data / PII when creating backups.Custom text pre-processors for full-text search ("Configurable Analyzers").Consistent snapshot backup in cluster mode.Co-located joins in a cluster using identically sharded collections ("SmartJoins").Graph traversal algorithm to get multiple shortest paths ("k Shortest Paths").Stop condition support for graph traversals ("Pruning in Traversals").Time-based removal of expired documents ("Time-to-live Index").Multi-document transactions with individual begin and commit / abort commands ("Stream Transactions").Inlining of certain subqueries to improve execution time.

ARANGODB PERFORMANCE FULL

Late document materialization to only fetch the relevant documents from SORT/LIMIT queries and early pruning of non-matching documents in full collection scans.

Parallel execution of queries on several cluster nodes.

Option to store all collections of a database on a single cluster node, to combine the performance of a single server and ACID semantics with a fault-tolerant cluster setup ("OneShard").

Key rotation for superuser JWT tokens, TLS certificates, and on-disk encryption keys.

Wildcard and fuzzy search support for full-text search.

Graphs replicated on all cluster nodes to execute graph traversals locally ("SatelliteGraphs").

Hardware-accelerated on-disk encryption.

Flexible data field pre-processing with custom queries ("AQL Analyzer") and the ability to chain built-in and custom analyzers ("Pipeline Analyzer").

Geo-spatial queries can be combined with full-text search.

Support for sliding window queries to aggregate adjacent documents, value ranges and time intervals.

Graph traversal algorithms to enumerate all paths between two vertices ("k Paths") and to emit paths in order of increasing edge weights ("Weighted Traversals").

Language-agnostic tokenization of text ("Segmentation Analyzer").

Collections replicated on all cluster nodes can be combined with graphs sharded by document attributes to enable more local execution of graph queries ("Hybrid SmartGraphs", "Hybrid Disjoint SmartGraphs").

ARANGODB PERFORMANCE SERIES

In October 2021 ArangoDB raised 27.8 million dollars in series B funding led by Iris Capital.

In March 2019 ArangoDB raised 10 million dollars in series A funding led by Bow Capital. In January 2017 ArangoDB raised a seed round investment of 4.2 million Euros led by Target Partners. The word "arango" refers to a little-known avocado variety grown in Cuba. Later, they changed the name to ArangoDB. They originally called the database system “A Versatile Object Container", or AVOC for short, leading them to call the database AvocadoDB. was founded in 2015 by Claudius Weinberger and Frank Celler. ArangoDB is a NoSQL database system but AQL is similar in many ways to SQL. AQL is mainly a declarative language and allows the combination of different data access patterns in a single query. ArangoDB is a multi-model database system since it supports three data models (graphs, JSON documents, key/value) with one database core and a unified query language AQL (ArangoDB Query Language).

ARANGODB PERFORMANCE FREE

Multi-model database, Graph database, Document-oriented database, Key/Value database, Full-text Search EngineĪrangoDB is a free and open-source native graph database system developed by ArangoDB Inc.