
RavenDB

ArangoDB

Map data natively to the database and access it with the best patterns for the job – traversals, joins, search, ranking, geospatial, aggregations – you name it
Polyglot persistence without the costs Easily design, scale and adapt your architectures to changing needs and with much less effort
Advanced Feature Engineering Combine the flexibility of JSON with semantic search and graph technology for next generation feature extraction even for large datasets
Learn more with ArangoDB University Graph Done Right: What and Why Graph? Graph and Entity Resolution Against Cyber Security Next-gen Network Management with Performance, Availability, and Security using ArangoDB ArangoDB SOC 2 Compliant
Systems: Windows, MacOS, Linux, Kubernetes, Docker Clients: Java, NET, JavaScript, NodeJS, Go, Python, Elixir, R, Rust
AQL is a declarative query language letting you access the very same data with a broad range of access patterns like traversals, JOINs, search, geospatial or any combination Everyone experienced with SQL will have an easy start with AQL and might think AQL feels more like coding
Get Started with AQL A combination of JSON stores, semantic search and graph technology is often used to provide native storage and access to data – Having everything in one place accessible with one query language provides crucial advantages With ArangoML and ArangoML Pipeline feature extraction and Pipeline observability got much simpler
Learn More About ArangoGraphML
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