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DBMS > AgensGraph vs. AnzoGraph DB vs. Google Cloud Spanner vs. HEAVY.AI vs. Kinetica

System Properties Comparison AgensGraph vs. AnzoGraph DB vs. Google Cloud Spanner vs. HEAVY.AI vs. Kinetica

Editorial information provided by DB-Engines
NameAgensGraph  Xexclude from comparisonAnzoGraph DB  Xexclude from comparisonGoogle Cloud Spanner  Xexclude from comparisonHEAVY.AI infoFormerly named 'OmniSci', rebranded to 'HEAVY.AI' in March 2022  Xexclude from comparisonKinetica  Xexclude from comparison
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 virtualizationA horizontally scalable, globally consistent, relational database service. It is the externalization of the core Google database that runs the biggest aspects of Google, like Ads and Google Play.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
Relational DBMSRelational DBMSRelational DBMS
Secondary database modelsSpatial DBMSSpatial DBMS
Time Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.23
Rank#315  Overall
#26  Graph DBMS
#140  Relational DBMS
Score0.29
Rank#303  Overall
#25  Graph DBMS
#14  RDF stores
Score2.84
Rank#100  Overall
#51  Relational DBMS
Score1.64
Rank#145  Overall
#67  Relational DBMS
Score0.66
Rank#234  Overall
#107  Relational DBMS
Websitebitnine.net/­agensgraphcambridgesemantics.com/­anzographcloud.google.com/­spannergithub.com/­heavyai/­heavydb
www.heavy.ai
www.kinetica.com
Technical documentationbitnine.net/­documentationdocs.cambridgesemantics.com/­anzograph/­userdoc/­home.htmcloud.google.com/­spanner/­docsdocs.heavy.aidocs.kinetica.com
DeveloperBitnine Global Inc.Cambridge SemanticsGoogleHEAVY.AI, Inc.Kinetica
Initial release20162018201720162012
Current release2.1, December 20182.3, January 20215.10, January 20227.1, August 2021
License infoCommercial or Open SourceOpen Source infoApache License 2.0commercial infofree trial version availablecommercialOpen Source infoApache Version 2; enterprise edition availablecommercial
Cloud-based only infoOnly available as a cloud servicenonoyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageCC++ and CUDAC, C++
Server operating systemsLinux
OS X
Windows
LinuxhostedLinuxLinux
Data schemedepending on used data modelSchema-free and OWL/RDFS-schema supportyesyesyes
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.nonononono
Secondary indexesyesnoyesnoyes
SQL infoSupport of SQLyesSPARQL and SPARQL* as primary query language. Cypher preview.yes infoQuery statements complying to ANSI 2011yesSQL-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
gRPC (using protocol buffers) API
JDBC infoAt present, JDBC supports read-only queries. No support for DDL or DML statements.
RESTful HTTP API
JDBC
ODBC
Thrift
Vega
JDBC
ODBC
RESTful HTTP API
Supported programming languagesC
Java
JavaScript
Python
C++
Java
Python
Go
Java
JavaScript (Node.js)
Python
All languages supporting JDBC/ODBC/Thrift
Python
C++
Java
JavaScript (Node.js)
Python
Server-side scripts infoStored proceduresyesuser defined functions and aggregatesnonouser 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-ClusterMulti-source replication with 3 replicas for regional instances.Multi-source replicationSource-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoKerberos/HDFS data loadingyes infousing Google Cloud Dataflownono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate Consistency in MPP-ClusterImmediate ConsistencyImmediate ConsistencyImmediate Consistency or Eventual Consistency depending on configuration
Foreign keys infoReferential integrityyesno infonot needed in graphsyes infoby using interleaved tables, this features focuses more on performance improvements than on referential integritynoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACIDACID infoStrict serializable isolationnono
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.noyesnoyesyes infoGPU vRAM or System RAM
User concepts infoAccess controlfine grained access rights according to SQL-standardAccess rights for users and rolesAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)fine grained access rights according to SQL-standardAccess rights for users and roles on table level

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