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DBMS > HugeGraph vs. InterSystems Caché vs. Neo4j vs. Splice Machine

System Properties Comparison HugeGraph vs. InterSystems Caché vs. Neo4j vs. Splice Machine

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Editorial information provided by DB-Engines
NameHugeGraph  Xexclude from comparisonInterSystems Caché  Xexclude from comparisonNeo4j  Xexclude from comparisonSplice Machine  Xexclude from comparison
Caché is a deprecated database engine which is substituted with InterSystems IRIS. It therefore is removed from the DB-Engines Ranking.
DescriptionA fast-speed and highly-scalable Graph DBMSA multi-model DBMS and application serverScalable, ACID-compliant graph database designed with a high-performance distributed cluster architecture, available in self-hosted and cloud offeringsOpen-Source SQL RDBMS for Operational and Analytical use cases with native Machine Learning, powered by Hadoop and Spark
Primary database modelGraph DBMSKey-value store
Object oriented DBMS
Relational DBMS
Graph DBMSRelational DBMS
Secondary database modelsDocument store
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.17
Rank#335  Overall
#31  Graph DBMS
Score44.89
Rank#21  Overall
#1  Graph DBMS
Score0.54
Rank#252  Overall
#115  Relational DBMS
Websitegithub.com/­hugegraph
hugegraph.apache.org
www.intersystems.com/­products/­cacheneo4j.comsplicemachine.com
Technical documentationhugegraph.apache.org/­docsdocs.intersystems.comneo4j.com/­docssplicemachine.com/­how-it-works
DeveloperBaiduInterSystemsNeo4j, Inc.Splice Machine
Initial release2018199720072014
Current release0.92018.1.4, May 20205.20, May 20243.1, March 2021
License infoCommercial or Open SourceOpen Source infoApache Version 2.0commercialOpen Source infoGPL version3, commercial licenses availableOpen Source infoAGPL 3.0, commercial license available
Cloud-based only infoOnly available as a cloud servicenononono
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 languageJavaJava, ScalaJava
Server operating systemsLinux
macOS
Unix
AIX
HP Open VMS
HP-UX
Linux
OS X
Solaris
Windows
Linux infoCan also be used server-less as embedded Java database.
OS X
Solaris
Windows
Linux
OS X
Solaris
Windows
Data schemeyesdepending on used data modelschema-free and schema-optionalyes
Typing infopredefined data types such as float or dateyesyesyesyes
XML support infoSome form of processing data in XML format, e.g. support for XML data structures, and/or support for XPath, XQuery or XSLT.noyes
Secondary indexesyes infoalso supports composite index and range indexyesyes infopluggable indexing subsystem, by default Apache Luceneyes
SQL infoSupport of SQLnoyesnoyes
APIs and other access methodsJava API
RESTful HTTP API
TinkerPop Gremlin
.NET Client API
JDBC
ODBC
RESTful HTTP API
Bolt protocol
Cypher query language
Java API
Neo4j-OGM infoObject Graph Mapper
RESTful HTTP API
Spring Data Neo4j
TinkerPop 3
JDBC
Native Spark Datasource
ODBC
Supported programming languagesGroovy
Java
Python
C#
C++
Java
.Net
Clojure
Elixir
Go
Groovy
Haskell
Java
JavaScript
Perl
PHP
Python
Ruby
Scala
C#
C++
Java
JavaScript (Node.js)
Python
R
Scala
Server-side scripts infoStored proceduresasynchronous Gremlin script jobsyesyes infoUser defined Procedures and Functionsyes infoJava
Triggersnoyesyes infovia event handleryes
Partitioning methods infoMethods for storing different data on different nodesyes infodepending on used storage backend, e.g. Cassandra and HBasenoneyes using Neo4j FabricShared Nothhing Auto-Sharding, Columnar Partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesyes infodepending on used storage backend, e.g. Cassandra and HBaseSource-replica replicationCausal Clustering using Raft protocol infoavailable in in Enterprise Version onlyMulti-source replication
Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsvia hugegraph-sparknonoYes, via Full Spark Integration
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual ConsistencyImmediate ConsistencyCausal and Eventual Consistency configurable in Causal Cluster setup
Immediate Consistency in stand-alone mode
Immediate Consistency
Foreign keys infoReferential integrityyes infoedges in graphyesyes infoRelationships in graphsyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACIDACIDACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes, multi-version concurrency control (MVCC)
Durability infoSupport for making data persistentyesyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesyesyes
User concepts infoAccess controlUsers, roles and permissionsAccess rights for users, groups and rolesUsers, roles and permissions. Pluggable authentication with supported standards (LDAP, Active Directory, Kerberos)Access rights for users, groups and roles according to SQL-standard
More information provided by the system vendor
HugeGraphInterSystems CachéNeo4jSplice Machine
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
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