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DBMS > EsgynDB vs. Kinetica vs. Microsoft Azure AI Search vs. PostgreSQL

System Properties Comparison EsgynDB vs. Kinetica vs. Microsoft Azure AI Search vs. PostgreSQL

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Editorial information provided by DB-Engines
NameEsgynDB  Xexclude from comparisonKinetica  Xexclude from comparisonMicrosoft Azure AI Search  Xexclude from comparisonPostgreSQL  Xexclude from comparison
DescriptionEnterprise-class SQL-on-Hadoop solution, powered by Apache TrafodionFully vectorized database across both GPUs and CPUsSearch-as-a-service for web and mobile app developmentWidely used open source RDBMS infoDeveloped as objectoriented DBMS (Postgres), gradually enhanced with 'standards' like SQL
Primary database modelRelational DBMSRelational DBMSSearch engineRelational DBMS infowith object oriented extensions, e.g.: user defined types/functions and inheritance. Handling of key/value pairs with hstore module.
Secondary database modelsSpatial DBMS
Time Series DBMS
Vector DBMSDocument 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
Score0.15
Rank#325  Overall
#144  Relational DBMS
Score0.42
Rank#261  Overall
#120  Relational DBMS
Score5.75
Rank#58  Overall
#7  Search engines
Score644.36
Rank#4  Overall
#4  Relational DBMS
Websitewww.esgyn.cnwww.kinetica.comazure.microsoft.com/­en-us/­services/­searchwww.postgresql.org
Technical documentationdocs.kinetica.comlearn.microsoft.com/­en-us/­azure/­searchwww.postgresql.org/­docs
DeveloperEsgynKineticaMicrosoftPostgreSQL Global Development Group infowww.postgresql.org/­developer
Initial release2015201220151989 info1989: Postgres, 1996: PostgreSQL
Current release7.1, August 2021V116.4, August 2024
License infoCommercial or Open SourcecommercialcommercialcommercialOpen Source infoBSD
Cloud-based only infoOnly available as a cloud servicenonoyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
PostgreSQL Flex @ STACKIT offers managed PostgreSQL Instances with adjustable CPU, RAM, storage amount and speed and several extensions available, in enterprise grade to perfectly match all application requirements. All 100% GDPR-compliant.
Implementation languageC++, JavaC, C++C
Server operating systemsLinuxLinuxhostedFreeBSD
HP-UX
Linux
NetBSD
OpenBSD
OS X
Solaris
Unix
Windows
Data schemeyesyesyesyes
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.nononoyes infospecific XML-type available, but no XML query functionality.
Secondary indexesyesyesyesyes
SQL infoSupport of SQLyesSQL-like DML and DDL statementsnoyes infostandard with numerous extensions
APIs and other access methodsADO.NET
JDBC
ODBC
JDBC
ODBC
RESTful HTTP API
RESTful HTTP APIADO.NET
JDBC
native C library
ODBC
streaming API for large objects
Supported programming languagesAll languages supporting JDBC/ODBC/ADO.NetC++
Java
JavaScript (Node.js)
Python
C#
Java
JavaScript
Python
.Net
C
C++
Delphi
Java infoJDBC
JavaScript (Node.js)
Perl
PHP
Python
Tcl
Server-side scripts infoStored proceduresJava Stored Proceduresuser defined functionsnouser defined functions inforealized in proprietary language PL/pgSQL or with common languages like Perl, Python, Tcl etc.
Triggersnoyes infotriggers when inserted values for one or more columns fall within a specified rangenoyes
Partitioning methods infoMethods for storing different data on different nodesShardingShardingSharding infoImplicit feature of the cloud servicepartitioning by range, list and (since PostgreSQL 11) by hash
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication between multi datacentersSource-replica replicationyes infoImplicit feature of the cloud serviceSource-replica replication infoother methods possible by using 3rd party extensions
MapReduce infoOffers an API for user-defined Map/Reduce methodsyesnonono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate Consistency or Eventual Consistency depending on configurationImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integrityyesyesnoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDnonoACID
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.noyes infoGPU vRAM or System RAMnono
User concepts infoAccess controlfine grained access rights according to SQL-standardAccess rights for users and roles on table levelyes infousing Azure authenticationfine grained access rights according to SQL-standard

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More resources
EsgynDBKineticaMicrosoft Azure AI SearchPostgreSQL
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Conferences, events and webinars

PASS Data Community Summit
Seattle, Washington, 4-8 November 2024

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