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DBMS > AgensGraph vs. HEAVY.AI vs. Immudb vs. Kinetica vs. PostgreSQL

System Properties Comparison AgensGraph vs. HEAVY.AI vs. Immudb vs. Kinetica vs. PostgreSQL

Editorial information provided by DB-Engines
NameAgensGraph  Xexclude from comparisonHEAVY.AI infoFormerly named 'OmniSci', rebranded to 'HEAVY.AI' in March 2022  Xexclude from comparisonImmudb  Xexclude from comparisonKinetica  Xexclude from comparisonPostgreSQL  Xexclude from comparison
DescriptionMulti-model database supporting relational and graph data models and built upon PostgreSQLA high performance, column-oriented RDBMS, specifically developed to harness the massive parallelism of modern CPU and GPU hardwareAn open source immutable (append-only) database with cryptographic verification which makes it tamper-resistant and fully auditable.Fully vectorized database across both GPUs and CPUsWidely used open source RDBMS infoDeveloped as objectoriented DBMS (Postgres), gradually enhanced with 'standards' like SQL
Primary database modelGraph DBMS
Relational DBMS
Relational DBMSKey-value storeRelational DBMSRelational DBMS infowith object oriented extensions, e.g.: user defined types/functions and inheritance. Handling of key/value pairs with hstore module.
Secondary database modelsSpatial DBMSRelational DBMSSpatial DBMS
Time Series DBMS
Document store
Graph DBMS infowith Apache Age
Spatial DBMS
Vector DBMS infowith pgvector extension
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.20
Rank#321  Overall
#27  Graph DBMS
#143  Relational DBMS
Score1.77
Rank#141  Overall
#65  Relational DBMS
Score0.24
Rank#305  Overall
#43  Key-value stores
Score0.64
Rank#236  Overall
#109  Relational DBMS
Score645.54
Rank#4  Overall
#4  Relational DBMS
Websitebitnine.net/­agensgraphgithub.com/­heavyai/­heavydb
www.heavy.ai
github.com/­codenotary/­immudb
immudb.io
www.kinetica.comwww.postgresql.org
Technical documentationbitnine.net/­documentationdocs.heavy.aidocs.immudb.iodocs.kinetica.comwww.postgresql.org/­docs
DeveloperBitnine Global Inc.HEAVY.AI, Inc.CodenotaryKineticaPostgreSQL Global Development Group infowww.postgresql.org/­developer
Initial release20162016202020121989 info1989: Postgres, 1996: PostgreSQL
Current release2.1, December 20185.10, January 20221.2.3, April 20227.1, August 202116.3, May 2024
License infoCommercial or Open SourceOpen Source infoApache License 2.0Open Source infoApache Version 2; enterprise edition availableOpen Source infoApache Version 2.0commercialOpen Source infoBSD
Cloud-based only infoOnly available as a cloud servicenonononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageCC++ and CUDAGoC, C++C
Server operating systemsLinux
OS X
Windows
LinuxBSD
Linux
macOS
Solaris
Windows
z/OS
LinuxFreeBSD
HP-UX
Linux
NetBSD
OpenBSD
OS X
Solaris
Unix
Windows
Data schemedepending on used data modelyesschema-freeyesyes
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.nonononoyes infospecific XML-type available, but no XML query functionality.
Secondary indexesyesnoyesyesyes
SQL infoSupport of SQLyesyesSQL-like syntaxSQL-like DML and DDL statementsyes infostandard with numerous extensions
APIs and other access methodsCypher Query Language
JDBC
JDBC
ODBC
Thrift
Vega
gRPC protocol
PostgreSQL wire protocol
JDBC
ODBC
RESTful HTTP API
ADO.NET
JDBC
native C library
ODBC
streaming API for large objects
Supported programming languagesC
Java
JavaScript
Python
All languages supporting JDBC/ODBC/Thrift
Python
.Net
Go
Java
JavaScript (Node.js)
Python
C++
Java
JavaScript (Node.js)
Python
.Net
C
C++
Delphi
Java infoJDBC
JavaScript (Node.js)
Perl
PHP
Python
Tcl
Server-side scripts infoStored proceduresyesnonouser defined functionsuser defined functions inforealized in proprietary language PL/pgSQL or with common languages like Perl, Python, Tcl etc.
Triggersnononoyes infotriggers when inserted values for one or more columns fall within a specified rangeyes
Partitioning methods infoMethods for storing different data on different nodesno, but can be realized using table inheritanceSharding infoRound robinShardingShardingpartitioning by range, list and (since PostgreSQL 11) by hash
Replication methods infoMethods for redundantly storing data on multiple nodesSource-replica replicationMulti-source replicationSource-replica replicationSource-replica replication infoother methods possible by using 3rd party extensions
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonononono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyImmediate ConsistencyImmediate Consistency or Eventual Consistency depending on configurationImmediate Consistency
Foreign keys infoReferential integrityyesnonoyesyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDnoACIDnoACID
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.noyesnoyes infoGPU vRAM or System RAMno
User concepts infoAccess controlfine grained access rights according to SQL-standardfine grained access rights according to SQL-standardAccess rights for users and roles on table levelfine grained access rights according to SQL-standard

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More resources
AgensGraphHEAVY.AI infoFormerly named 'OmniSci', rebranded to 'HEAVY.AI' in March 2022ImmudbKineticaPostgreSQL
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