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Learn MorePros of Akutan
Pros of Cayley
Pros of Neo4j
Pros of Akutan
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Pros of Cayley
- Full open source7
Pros of Neo4j
- Cypher – graph query language70
- Great graphdb61
- Open source33
- Rest api31
- High-Performance Native API27
- ACID23
- Easy setup21
- Great support17
- Clustering11
- Hot Backups9
- Great Web Admin UI8
- Powerful, flexible data model7
- Mature7
- Embeddable6
- Easy to Use and Model5
- Best Graphdb4
- Highly-available4
- It's awesome, I wanted to try it2
- Great onboarding process2
- Great query language and built in data browser2
- Used by Crunchbase2
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Cons of Akutan
Cons of Cayley
Cons of Neo4j
Cons of Akutan
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Cons of Cayley
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Cons of Neo4j
- Comparably slow9
- Can't store a vertex as JSON4
- Doesn't have a managed cloud service at low cost1
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- No public GitHub repository available -
What is Akutan?
A distributed knowledge graph store. Knowledge graphs are suitable for modeling data that is highly interconnected by many types of relationships, like encyclopedic information about the world.
What is Cayley?
Cayley is an open-source graph inspired by the graph database behind Freebase and Google's Knowledge Graph. Its goal is to be a part of the developer's toolbox where Linked Data and graph-shaped data (semantic webs, social networks, etc) in general are concerned.
What is Neo4j?
Neo4j stores data in nodes connected by directed, typed relationships with properties on both, also known as a Property Graph. It is a high performance graph store with all the features expected of a mature and robust database, like a friendly query language and ACID transactions.
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What companies use Akutan?
What companies use Cayley?
What companies use Neo4j?
What companies use Akutan?
No companies found
What companies use Cayley?
No companies found
What companies use Neo4j?
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What tools integrate with Akutan?
What tools integrate with Cayley?
What tools integrate with Neo4j?
What tools integrate with Akutan?
What tools integrate with Cayley?
No integrations found
What tools integrate with Neo4j?
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What are some alternatives to Akutan, Cayley, and Neo4j?
Apache Beam
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Apache Spark
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Apache Flink
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Arc
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Dgraph
Dgraph's goal is to provide Google production level scale and throughput, with low enough latency to be serving real time user queries, over terabytes of structured data. Dgraph supports GraphQL-like query syntax, and responds in JSON and Protocol Buffers over GRPC and HTTP.