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DBMS > AgensGraph vs. AnzoGraph DB vs. Blazegraph vs. HEAVY.AI vs. Kinetica

System Properties Comparison AgensGraph vs. AnzoGraph DB vs. Blazegraph vs. HEAVY.AI vs. Kinetica

Editorial information provided by DB-Engines
NameAgensGraph  Xexclude from comparisonAnzoGraph DB  Xexclude from comparisonBlazegraph  Xexclude from comparisonHEAVY.AI infoFormerly named 'OmniSci', rebranded to 'HEAVY.AI' in March 2022  Xexclude from comparisonKinetica  Xexclude from comparison
Amazon has acquired Blazegraph's domain and (probably) product. It is said that Amazon Neptune is based on Blazegraph.
DescriptionMulti-model database supporting relational and graph data models and built upon PostgreSQLScalable graph database built for online analytics and data harmonization with MPP scaling, high-performance analytical algorithms and reasoning, and virtualizationHigh-performance graph database supporting Semantic Web (RDF/SPARQL) and Graph Database (tinkerpop3, blueprints, vertex-centric) APIs with scale-out and High Availability.A high performance, column-oriented RDBMS, specifically developed to harness the massive parallelism of modern CPU and GPU hardwareFully vectorized database across both GPUs and CPUs
Primary database modelGraph DBMS
Relational DBMS
Graph DBMS
RDF store
Graph DBMS
RDF store
Relational DBMSRelational DBMS
Secondary database modelsSpatial DBMSSpatial DBMS
Time Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.20
Rank#321  Overall
#27  Graph DBMS
#143  Relational DBMS
Score0.23
Rank#307  Overall
#24  Graph DBMS
#13  RDF stores
Score0.75
Rank#219  Overall
#19  Graph DBMS
#8  RDF stores
Score1.77
Rank#141  Overall
#65  Relational DBMS
Score0.64
Rank#236  Overall
#109  Relational DBMS
Websitebitnine.net/­agensgraphcambridgesemantics.com/­anzographblazegraph.comgithub.com/­heavyai/­heavydb
www.heavy.ai
www.kinetica.com
Technical documentationbitnine.net/­documentationdocs.cambridgesemantics.com/­anzograph/­userdoc/­home.htmwiki.blazegraph.comdocs.heavy.aidocs.kinetica.com
DeveloperBitnine Global Inc.Cambridge SemanticsBlazegraphHEAVY.AI, Inc.Kinetica
Initial release20162018200620162012
Current release2.1, December 20182.3, January 20212.1.5, March 20195.10, January 20227.1, August 2021
License infoCommercial or Open SourceOpen Source infoApache License 2.0commercial infofree trial version availableOpen Source infoextended commercial license availableOpen Source infoApache Version 2; enterprise edition availablecommercial
Cloud-based only infoOnly available as a cloud servicenonononono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageCJavaC++ and CUDAC, C++
Server operating systemsLinux
OS X
Windows
LinuxLinux
OS X
Windows
LinuxLinux
Data schemedepending on used data modelSchema-free and OWL/RDFS-schema supportschema-freeyesyes
Typing infopredefined data types such as float or dateyesyes infoRDF literal typesyesyes
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.nononono
Secondary indexesyesnoyesnoyes
SQL infoSupport of SQLyesSPARQL and SPARQL* as primary query language. Cypher preview.SPARQL is used as query languageyesSQL-like DML and DDL statements
APIs and other access methodsCypher Query Language
JDBC
Apache Mule
gRPC
JDBC
Kafka
OData access for BI tools
OpenCypher
RESTful HTTP API
SPARQL
Java API
RESTful HTTP API
SPARQL QUERY
SPARQL UPDATE
TinkerPop 3
JDBC
ODBC
Thrift
Vega
JDBC
ODBC
RESTful HTTP API
Supported programming languagesC
Java
JavaScript
Python
C++
Java
Python
.Net
C
C++
Java
JavaScript
PHP
Python
Ruby
All languages supporting JDBC/ODBC/Thrift
Python
C++
Java
JavaScript (Node.js)
Python
Server-side scripts infoStored proceduresyesuser defined functions and aggregatesyesnouser defined functions
Triggersnonononoyes infotriggers when inserted values for one or more columns fall within a specified range
Partitioning methods infoMethods for storing different data on different nodesno, but can be realized using table inheritanceAutomatic shardingShardingSharding infoRound robinSharding
Replication methods infoMethods for redundantly storing data on multiple nodesSource-replica replicationMulti-source replication in MPP-ClusteryesMulti-source replicationSource-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoKerberos/HDFS data loadingnonono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate Consistency in MPP-ClusterImmediate Consistency or Eventual Consistency depending on configurationImmediate ConsistencyImmediate Consistency or Eventual Consistency depending on configuration
Foreign keys infoReferential integrityyesno infonot needed in graphsyes infoRelationships in Graphsnoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACIDACIDnono
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
Durability infoSupport for making data persistentyesyesyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyesyesyes infoGPU vRAM or System RAM
User concepts infoAccess controlfine grained access rights according to SQL-standardAccess rights for users and rolesSecurity and Authentication via Web Application Container (Tomcat, Jetty)fine grained access rights according to SQL-standardAccess rights for users and roles on table level

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More resources
AgensGraphAnzoGraph DBBlazegraphHEAVY.AI infoFormerly named 'OmniSci', rebranded to 'HEAVY.AI' in March 2022Kinetica
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