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DBMS > GridGain vs. HugeGraph vs. LeanXcale vs. Neo4j

System Properties Comparison GridGain vs. HugeGraph vs. LeanXcale vs. Neo4j

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Editorial information provided by DB-Engines
NameGridGain  Xexclude from comparisonHugeGraph  Xexclude from comparisonLeanXcale  Xexclude from comparisonNeo4j  Xexclude from comparison
DescriptionGridGain is an in-memory computing platform, built on Apache IgniteA fast-speed and highly-scalable Graph DBMSA highly scalable full ACID SQL database with fast NoSQL data ingestion and GIS capabilitiesScalable, ACID-compliant graph database designed with a high-performance distributed cluster architecture, available in self-hosted and cloud offerings
Primary database modelKey-value store
Relational DBMS
Graph DBMSKey-value store
Relational DBMS
Graph DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.55
Rank#150  Overall
#26  Key-value stores
#70  Relational DBMS
Score0.17
Rank#335  Overall
#31  Graph DBMS
Score0.36
Rank#280  Overall
#40  Key-value stores
#129  Relational DBMS
Score44.89
Rank#21  Overall
#1  Graph DBMS
Websitewww.gridgain.comgithub.com/­hugegraph
hugegraph.apache.org
www.leanxcale.comneo4j.com
Technical documentationwww.gridgain.com/­docs/­index.htmlhugegraph.apache.org/­docsneo4j.com/­docs
DeveloperGridGain Systems, Inc.BaiduLeanXcaleNeo4j, Inc.
Initial release2007201820152007
Current releaseGridGain 8.5.10.95.20, May 2024
License infoCommercial or Open SourcecommercialOpen Source infoApache Version 2.0commercialOpen Source infoGPL version3, commercial licenses 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 languageJava, C++, .NetJavaJava, Scala
Server operating systemsLinux
OS X
Solaris
Windows
Linux
macOS
Unix
Linux infoCan also be used server-less as embedded Java database.
OS X
Solaris
Windows
Data schemeyesyesyesschema-free and schema-optional
Typing infopredefined data types such as float or dateyesyesyes
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.yesno
Secondary indexesyesyes infoalso supports composite index and range indexyes infopluggable indexing subsystem, by default Apache Lucene
SQL infoSupport of SQLANSI-99 for query and DML statements, subset of DDLnoyes infothrough Apache Derbyno
APIs and other access methodsHDFS API
Hibernate
JCache
JDBC
ODBC
Proprietary protocol
RESTful HTTP API
Spring Data
Java API
RESTful HTTP API
TinkerPop Gremlin
JDBC
Kafka Connector
ODBC
proprietary key/value interface
Spark Connector
Bolt protocol
Cypher query language
Java API
Neo4j-OGM infoObject Graph Mapper
RESTful HTTP API
Spring Data Neo4j
TinkerPop 3
Supported programming languagesC#
C++
Java
PHP
Python
Ruby
Scala
Groovy
Java
Python
C
Java
Scala
.Net
Clojure
Elixir
Go
Groovy
Haskell
Java
JavaScript
Perl
PHP
Python
Ruby
Scala
Server-side scripts infoStored proceduresyes (compute grid and cache interceptors can be used instead)asynchronous Gremlin script jobsyes infoUser defined Procedures and Functions
Triggersyes (cache interceptors and events)noyes infovia event handler
Partitioning methods infoMethods for storing different data on different nodesShardingyes infodepending on used storage backend, e.g. Cassandra and HBaseyes using Neo4j Fabric
Replication methods infoMethods for redundantly storing data on multiple nodesyes (replicated cache)yes infodepending on used storage backend, e.g. Cassandra and HBaseCausal Clustering using Raft protocol infoavailable in in Enterprise Version only
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes (compute grid and hadoop accelerator)via hugegraph-sparknono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyEventual ConsistencyImmediate ConsistencyCausal and Eventual Consistency configurable in Causal Cluster setup
Immediate Consistency in stand-alone mode
Foreign keys infoReferential integritynoyes infoedges in graphyesyes infoRelationships in graphs
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACIDACIDACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
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 controlSecurity Hooks for custom implementationsUsers, roles and permissionsUsers, roles and permissions. Pluggable authentication with supported standards (LDAP, Active Directory, Kerberos)
More information provided by the system vendor
GridGainHugeGraphLeanXcaleNeo4j
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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