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DBMS > Neo4j vs. RavenDB vs. Titan

System Properties Comparison Neo4j vs. RavenDB vs. Titan

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Editorial information provided by DB-Engines
NameNeo4j  Xexclude from comparisonRavenDB  Xexclude from comparisonTitan  Xexclude from comparison
Titan has been decommisioned after the takeover by Datastax. It will be removed from the DB-Engines ranking. A fork has been open-sourced as JanusGraph.
DescriptionScalable, ACID-compliant graph database designed with a high-performance distributed cluster architecture, available in self-hosted and cloud offeringsOpen Source Operational and Transactional Enterprise NoSQL Document DatabaseTitan is a Graph DBMS optimized for distributed clusters.
Primary database modelGraph DBMSDocument storeGraph DBMS
Secondary database modelsGraph DBMS
Spatial DBMS
Time Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score44.46
Rank#23  Overall
#1  Graph DBMS
Score2.92
Rank#101  Overall
#18  Document stores
Websiteneo4j.comravendb.netgithub.com/­thinkaurelius/­titan
Technical documentationneo4j.com/­docsravendb.net/­docsgithub.com/­thinkaurelius/­titan/­wiki
DeveloperNeo4j, Inc.Hibernating RhinosAurelius, owned by DataStax
Initial release200720102012
Current release5.19, April 20245.4, July 2022
License infoCommercial or Open SourceOpen Source infoGPL version3, commercial licenses availableOpen Source infoAGPL version 3, commercial license availableOpen Source infoApache license, version 2.0
Cloud-based only infoOnly available as a cloud servicenonono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Neo4j Aura: Neo4j’s fully managed cloud service: The zero-admin, always-on graph database for cloud developers.
Implementation languageJava, ScalaC#Java
Server operating systemsLinux infoCan also be used server-less as embedded Java database.
OS X
Solaris
Windows
Linux
macOS
Raspberry Pi
Windows
Linux
OS X
Unix
Windows
Data schemeschema-free and schema-optionalschema-freeyes
Typing infopredefined data types such as float or dateyesnoyes
Secondary indexesyes infopluggable indexing subsystem, by default Apache Luceneyesyes
SQL infoSupport of SQLnoSQL-like query language (RQL)no
APIs and other access methodsBolt protocol
Cypher query language
Java API
Neo4j-OGM infoObject Graph Mapper
RESTful HTTP API
Spring Data Neo4j
TinkerPop 3
.NET Client API
F# Client API
Go Client API
Java Client API
NodeJS Client API
PHP Client API
Python Client API
RESTful HTTP API
Java API
TinkerPop Blueprints
TinkerPop Frames
TinkerPop Gremlin
TinkerPop Rexster
Supported programming languages.Net
Clojure
Elixir
Go
Groovy
Haskell
Java
JavaScript
Perl
PHP
Python
Ruby
Scala
.Net
C#
F#
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
Clojure
Java
Python
Server-side scripts infoStored proceduresyes infoUser defined Procedures and Functionsyesyes
Triggersyes infovia event handleryesyes
Partitioning methods infoMethods for storing different data on different nodesyes using Neo4j FabricShardingyes infovia pluggable storage backends
Replication methods infoMethods for redundantly storing data on multiple nodesCausal Clustering using Raft protocol infoavailable in in Enterprise Version onlyMulti-source replicationyes
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyesyes infovia Faunus, a graph analytics engine
Consistency concepts infoMethods to ensure consistency in a distributed systemCausal and Eventual Consistency configurable in Causal Cluster setup
Immediate Consistency in stand-alone mode
Default ACID transactions on the local node (eventually consistent across the cluster). Atomic operations with cluster-wide ACID transactions. Eventual consistency for indexes and full-text search indexes.Eventual Consistency
Immediate Consistency
Foreign keys infoReferential integrityyes infoRelationships in graphsnoyes infoRelationships in graph
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACID, Cluster-wide transaction availableACID
Concurrency infoSupport for concurrent manipulation of datayesyesyes
Durability infoSupport for making data persistentyesyesyes infoSupports various storage backends: Cassandra, HBase, Berkeley DB, Akiban, Hazelcast
User concepts infoAccess controlUsers, roles and permissions. Pluggable authentication with supported standards (LDAP, Active Directory, Kerberos)Authorization levels configured per client per databaseUser authentification and security via Rexster Graph Server
More information provided by the system vendor
Neo4jRavenDBTitan
Specific characteristicsNeo4j delivers graph technology that has been battle tested for performance and scale...
» more
Competitive advantagesNeo4j is the market leader, graph database category creator, and the most widely...
» more
Typical application scenariosReal-Time Recommendations Master Data Management Identity and Access Management Network...
» more
Key customersOver 800 commercial customers and over 4300 startups use Neo4j. Flagship customers...
» more
Market metricsNeo4j boasts the world's largest graph database ecosystem with more than 140 million...
» more
Licensing and pricing modelsGPL v3 license that can be used all the places where you might use MySQL. Neo4j Commercial...
» more
News

This Week in Neo4j: GraphRAG, Knowledge Graphs, Open Source AI, GraphQL and more
4 May 2024

This Week in Neo4j: Nodes 2024, Data Modelling, Events, Knowledge Graphs and more
27 April 2024

GQL is Here: Your Cypher Queries in a GQL World
26 April 2024

GQL: The ISO Standard for Graphs Has Arrived
25 April 2024

What Is Retrieval-Augmented Generation (RAG)?
24 April 2024

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and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.

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More resources
Neo4jRavenDBTitan
DB-Engines blog posts

Applying Graph Analytics to Game of Thrones
12 June 2019, Amy Hodler & Mark Needham, Neo4j (guest author)

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2 March 2016, Paul Andlinger

The openCypher Project: Help Shape the SQL for Graphs
22 December 2015, Emil Eifrem (guest author)

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Graph DBMS increased their popularity by 500% within the last 2 years
3 March 2015, Paul Andlinger

Graph DBMSs are gaining in popularity faster than any other database category
21 January 2014, Matthias Gelbmann

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