ArangoDB 3.9 scales graph database operations
Open-source graph database vendor ArangoDB has updated its namesake database with new features that improve both scalability and search.
ArangoDB 3.9 became generally available on February 15 for open source and enterprise users, as well as on the database cloud platform as a service ArangoDB Oasis.
ArangoDB provides multi-model database functionality, but primarily focuses on serving graph database Platform. The vendor has seen growth in recent years, securing a $27.8 million funding round as of October 2021.
Graph database technology is an active market with a bright future, says IDC analyst Carl Olofson. He noted that the market today is dominated by purpose-built graph database platforms such as Neo4j, TigerGraph and Amazon Neptune.
Carl OlofsonAnalyst, IDC
“ArangoDB marketed their product first as a document database and later as a multi-model database, but it seems to me that their strongest game is as a graph database,” said Olofson. “ArangoDB has made significant progress in the graph space, and I think that’s their strong point.”
ArangoDB 3.9 Scaling Graph Database Operations
ArangoDB 3.9 includes a number of updates to improve scalability.
“We are seeing our customers moving towards larger and larger clusters and use cases,” said Jörg Schad, CTO at ArangoDB. “So in terms of data and deployment, we’ve integrated a lot of things to enable this at scale.”
Among the scalability improvements is the ability to run queries faster on a large number of database nodes. ArangoDB 3.9 also contains optimizations for balancing database clusters as workloads grow.
Hybrid Smart Graphs are coming to ArangoDB 3.9
One of ArangoDB 3.9’s scalability capabilities comes in the form of a feature the vendor calls Hybrid Smart Graph.
ArangoDB already had a capability known as smart graphs, which allows graph data to be distributed across multiple database nodes. Schad noted that ArangoDB users also simply replicated data, usually for small datasets, to scale graph datasets. Replicated data provides a complete copy of data, while partitioning provides slices of data distributed across nodes.
Hybrid Smart Graphs allow users of the ArangoDB query optimizer to use a combination of smart partitioning and data replication for searched data, Schad said.
ArangoSearch gets a boost for graphics queries
As part of the ArangoDB 3.9 release, the company has also updated its ArangoSearch functionality.
ArangoSearch is a full-text search feature that can search across different types of data, including charts, JSON-formatted document data, and geospatial data. Schad said he’s seen applications where organizations start with full-text search to identify potential starting nodes for matching graph patterns for analytics as well as fraud detection.
The ArangoSearch update provides what the company calls a segmentation analyzer for language search.
It’s not uncommon for a single document or data graphic to contain content in multiple languages, and Schad noted that ArangoSearch supports more than 40 human languages. With the update, it can segment queries and results by language.
Looking ahead, Schad said future versions of ArangoDB will likely get improved storage performance to speed up graph queries. He also said that the vendor will continue to work on improving the overall user experience of interacting with the ArangoDB database.
“We have a lot of really cool features coming,” Schad said.