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DBMS > AgensGraph vs. Kinetica vs. Valentina Server vs. Vertica

System Properties Comparison AgensGraph vs. Kinetica vs. Valentina Server vs. Vertica

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Editorial information provided by DB-Engines
NameAgensGraph  Xexclude from comparisonKinetica  Xexclude from comparisonValentina Server  Xexclude from comparisonVertica infoOpenText™ Vertica™  Xexclude from comparison
DescriptionMulti-model database supporting relational and graph data models and built upon PostgreSQLFully vectorized database across both GPUs and CPUsObject-relational database and reports serverCloud or off-cloud analytical database and query engine for structured and semi-structured streaming and batch data. Machine learning platform with built-in algorithms, data preparation capabilities, and model evaluation and management via SQL or Python.
Primary database modelGraph DBMS
Relational DBMS
Relational DBMSRelational DBMSRelational DBMS infoColumn oriented
Secondary database modelsSpatial DBMS
Time Series DBMS
Spatial DBMS
Time Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.17
Rank#320  Overall
#29  Graph DBMS
#143  Relational DBMS
Score0.42
Rank#261  Overall
#120  Relational DBMS
Score0.18
Rank#313  Overall
#140  Relational DBMS
Score9.62
Rank#42  Overall
#26  Relational DBMS
Websitebitnine.net/­agensgraphwww.kinetica.comwww.valentina-db.netwww.vertica.com
Technical documentationbitnine.net/­documentationdocs.kinetica.comvalentina-db.com/­docs/­dokuwiki/­v5/­doku.phpvertica.com/­documentation
DeveloperBitnine Global Inc.KineticaParadigma SoftwareOpenText infopreviously Micro Focus and Hewlett Packard
Initial release2016201219992005
Current release2.1, December 20187.1, August 20215.7.512.0.3, January 2023
License infoCommercial or Open SourceOpen Source infoApache License 2.0commercialcommercialcommercial infoLimited community edition free
Cloud-based only infoOnly available as a cloud servicenononono infoon-premises, all major clouds - Amazon AWS, Microsoft Azure, Google Cloud Platform and containers
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageCC, C++C++
Server operating systemsLinux
OS X
Windows
LinuxLinux
OS X
Windows
Linux
Data schemedepending on used data modelyesyesYes, but also semi-structure/unstructured data storage, and complex hierarchical data (like Parquet) stored and/or queried.
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 indexesyesyesyesNo Indexes Required. Different internal optimization strategy, but same functionality included.
SQL infoSupport of SQLyesSQL-like DML and DDL statementsyesFull 1999 standard plus machine learning, time series and geospatial. Over 650 functions.
APIs and other access methodsCypher Query Language
JDBC
JDBC
ODBC
RESTful HTTP API
ODBCADO.NET
JDBC
Kafka Connector
ODBC
RESTful HTTP API
Spark Connector
vSQL infocharacter-based, interactive, front-end utility
Supported programming languagesC
Java
JavaScript
Python
C++
Java
JavaScript (Node.js)
Python
.Net
C
C#
C++
Objective-C
PHP
Ruby
Visual Basic
Visual Basic.NET
C#
C++
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
R
Server-side scripts infoStored proceduresyesuser defined functionsyesyes, PostgreSQL PL/pgSQL, with minor differences
Triggersnoyes infotriggers when inserted values for one or more columns fall within a specified rangeyesyes, called Custom Alerts
Partitioning methods infoMethods for storing different data on different nodesno, but can be realized using table inheritanceShardinghorizontal partitioning, hierarchical partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesSource-replica replicationSource-replica replicationMulti-source replication infoOne, or more copies of data replicated across nodes, or object-store used for repository.
MapReduce infoOffers an API for user-defined Map/Reduce methodsnononono infoBi-directional Spark integration
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate Consistency or Eventual Consistency depending on configurationImmediate Consistency
Foreign keys infoReferential integrityyesyesyesyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDnoACID
Concurrency infoSupport for concurrent manipulation of datayesyesyes
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.noyes infoGPU vRAM or System RAMyesno
User concepts infoAccess controlfine grained access rights according to SQL-standardAccess rights for users and roles on table levelfine grained access rights according to SQL-standardfine grained access rights according to SQL-standard; supports Kerberos, LDAP, Ident and hash

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More resources
AgensGraphKineticaValentina ServerVertica infoOpenText™ Vertica™
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