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DBMS > Apache Phoenix vs. HugeGraph vs. Linter vs. Neo4j

System Properties Comparison Apache Phoenix vs. HugeGraph vs. Linter vs. Neo4j

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Editorial information provided by DB-Engines
NameApache Phoenix  Xexclude from comparisonHugeGraph  Xexclude from comparisonLinter  Xexclude from comparisonNeo4j  Xexclude from comparison
DescriptionA scale-out RDBMS with evolutionary schema built on Apache HBaseA fast-speed and highly-scalable Graph DBMSRDBMS for high security requirementsScalable, ACID-compliant graph database designed with a high-performance distributed cluster architecture, available in self-hosted and cloud offerings
Primary database modelRelational DBMSGraph DBMSRelational DBMSGraph DBMS
Secondary database modelsSpatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score2.06
Rank#123  Overall
#58  Relational DBMS
Score0.17
Rank#335  Overall
#31  Graph DBMS
Score0.12
Rank#350  Overall
#152  Relational DBMS
Score44.89
Rank#21  Overall
#1  Graph DBMS
Websitephoenix.apache.orggithub.com/­hugegraph
hugegraph.apache.org
linter.runeo4j.com
Technical documentationphoenix.apache.orghugegraph.apache.org/­docsneo4j.com/­docs
DeveloperApache Software FoundationBaidurelex.ruNeo4j, Inc.
Initial release2014201819902007
Current release5.0-HBase2, July 2018 and 4.15-HBase1, December 20190.95.20, May 2024
License infoCommercial or Open SourceOpen Source infoApache Version 2.0Open 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 languageJavaJavaC and C++Java, Scala
Server operating systemsLinux
Unix
Windows
Linux
macOS
Unix
AIX
Android
BSD
HP Open VMS
iOS
Linux
OS X
VxWorks
Windows
Linux infoCan also be used server-less as embedded Java database.
OS X
Solaris
Windows
Data schemeyes infolate-bound, schema-on-read capabilitiesyesyesschema-free and schema-optional
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.nonono
Secondary indexesyesyes infoalso supports composite index and range indexyesyes infopluggable indexing subsystem, by default Apache Lucene
SQL infoSupport of SQLyesnoyesno
APIs and other access methodsJDBCJava API
RESTful HTTP API
TinkerPop Gremlin
ADO.NET
JDBC
LINQ
ODBC
OLE DB
Oracle Call Interface (OCI)
Bolt protocol
Cypher query language
Java API
Neo4j-OGM infoObject Graph Mapper
RESTful HTTP API
Spring Data Neo4j
TinkerPop 3
Supported programming languagesC
C#
C++
Go
Groovy
Java
PHP
Python
Scala
Groovy
Java
Python
C
C#
C++
Java
Perl
PHP
Python
Qt
Ruby
Tcl
.Net
Clojure
Elixir
Go
Groovy
Haskell
Java
JavaScript
Perl
PHP
Python
Ruby
Scala
Server-side scripts infoStored proceduresuser defined functionsasynchronous Gremlin script jobsyes infoproprietary syntax with the possibility to convert from PL/SQLyes infoUser defined Procedures and Functions
Triggersnonoyesyes infovia event handler
Partitioning methods infoMethods for storing different data on different nodesShardingyes infodepending on used storage backend, e.g. Cassandra and HBasenoneyes using Neo4j Fabric
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication
Source-replica replication
yes infodepending on used storage backend, e.g. Cassandra and HBaseSource-replica replicationCausal Clustering using Raft protocol infoavailable in in Enterprise Version only
MapReduce infoOffers an API for user-defined Map/Reduce methodsHadoop integrationvia hugegraph-sparknono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate Consistency or Eventual 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.yesyes
User concepts infoAccess controlAccess Control Lists (using HBase ACL) for RBAC, integration with Apache Ranger for RBAC & ABAC, multi-tenancyUsers, roles and permissionsfine grained access rights according to SQL-standardUsers, roles and permissions. Pluggable authentication with supported standards (LDAP, Active Directory, Kerberos)
More information provided by the system vendor
Apache PhoenixHugeGraphLinterNeo4j
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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and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.

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