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Pros of Dgraph
Pros of Neo4j
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Pros of Dgraph
- Graphql as a query language is nice if you like apollo3
- Easy set up2
- Low learning curve2
- Open Source1
- High Performance1
Pros of Neo4j
- Cypher – graph query language69
- 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
- Highly-available4
- Best Graphdb4
- 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 Dgraph
Cons of Neo4j
Cons of Akutan
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Cons of Dgraph
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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 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.
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 Dgraph?
What companies use Neo4j?
What companies use Akutan?
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What tools integrate with Akutan?
What tools integrate with Dgraph?
What tools integrate with Neo4j?
What tools integrate with Akutan?
What tools integrate with Dgraph?
No integrations found
What tools integrate with Neo4j?
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What are some alternatives to Akutan, Dgraph, and Neo4j?
Apache Beam
It implements batch and streaming data processing jobs that run on any execution engine. It executes pipelines on multiple execution environments.
Apache Spark
Spark is a fast and general processing engine compatible with Hadoop data. It can run in Hadoop clusters through YARN or Spark's standalone mode, and it can process data in HDFS, HBase, Cassandra, Hive, and any Hadoop InputFormat. It is designed to perform both batch processing (similar to MapReduce) and new workloads like streaming, interactive queries, and machine learning.
Apache Flink
Apache Flink is an open source system for fast and versatile data analytics in clusters. Flink supports batch and streaming analytics, in one system. Analytical programs can be written in concise and elegant APIs in Java and Scala.
Arc
Arc is designed for exploratory programming: the kind where you decide what to write by writing it. A good medium for exploratory programming is one that makes programs brief and malleable, so that's what we've aimed for. This is a medium for sketching software.
MySQL
The MySQL software delivers a very fast, multi-threaded, multi-user, and robust SQL (Structured Query Language) database server. MySQL Server is intended for mission-critical, heavy-load production systems as well as for embedding into mass-deployed software.