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DBMS > EsgynDB vs. Kinetica vs. Microsoft Azure AI Search vs. Solr vs. Yaacomo

System Properties Comparison EsgynDB vs. Kinetica vs. Microsoft Azure AI Search vs. Solr vs. Yaacomo

Editorial information provided by DB-Engines
NameEsgynDB  Xexclude from comparisonKinetica  Xexclude from comparisonMicrosoft Azure AI Search  Xexclude from comparisonSolr  Xexclude from comparisonYaacomo  Xexclude from comparison
Yaacomo seems to be discontinued and is removed from the DB-Engines ranking
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 developmentA widely used distributed, scalable search engine based on Apache LuceneOpenCL based in-memory RDBMS, designed for efficiently utilizing the hardware via parallel computing
Primary database modelRelational DBMSRelational DBMSSearch engineSearch engineRelational DBMS
Secondary database modelsSpatial DBMS
Time Series DBMS
Vector DBMSSpatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.25
Rank#312  Overall
#138  Relational DBMS
Score0.66
Rank#234  Overall
#107  Relational DBMS
Score5.52
Rank#59  Overall
#6  Search engines
Score41.02
Rank#24  Overall
#3  Search engines
Websitewww.esgyn.cnwww.kinetica.comazure.microsoft.com/­en-us/­services/­searchsolr.apache.orgyaacomo.com
Technical documentationdocs.kinetica.comlearn.microsoft.com/­en-us/­azure/­searchsolr.apache.org/­resources.html
DeveloperEsgynKineticaMicrosoftApache Software FoundationQ2WEB GmbH
Initial release20152012201520062009
Current release7.1, August 2021V19.6.1, May 2024
License infoCommercial or Open SourcecommercialcommercialcommercialOpen Source infoApache Version 2commercial
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 languageC++, JavaC, C++Java
Server operating systemsLinuxLinuxhostedAll OS with a Java VM inforuns as a servlet in servlet container (e.g. Tomcat, Jetty is included)Android
Linux
Windows
Data schemeyesyesyesyes infoDynamic Fields enables on-the-fly addition of new fieldsyes
Typing infopredefined data types such as float or dateyesyesyesyes infosupports customizable data types and automatic typingyes
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.nononoyesno
Secondary indexesyesyesyesyes infoAll search fields are automatically indexedyes
SQL infoSupport of SQLyesSQL-like DML and DDL statementsnoSolr Parallel SQL Interfaceyes
APIs and other access methodsADO.NET
JDBC
ODBC
JDBC
ODBC
RESTful HTTP API
RESTful HTTP APIJava API
RESTful HTTP/JSON API
JDBC
ODBC
Supported programming languagesAll languages supporting JDBC/ODBC/ADO.NetC++
Java
JavaScript (Node.js)
Python
C#
Java
JavaScript
Python
.Net
Erlang
Java
JavaScript
any language that supports sockets and either XML or JSON
Perl
PHP
Python
Ruby
Scala
Server-side scripts infoStored proceduresJava Stored Proceduresuser defined functionsnoJava plugins
Triggersnoyes infotriggers when inserted values for one or more columns fall within a specified rangenoyes infoUser configurable commands triggered on index changesyes
Partitioning methods infoMethods for storing different data on different nodesShardingShardingSharding infoImplicit feature of the cloud serviceShardinghorizontal partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication between multi datacentersSource-replica replicationyes infoImplicit feature of the cloud serviceyesSource-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsyesnonospark-solr: github.com/­lucidworks/­spark-solr and streaming expressions to reduceno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate Consistency or Eventual Consistency depending on configurationImmediate ConsistencyEventual ConsistencyImmediate Consistency
Foreign keys infoReferential integrityyesyesnonoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDnonooptimistic lockingACID
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.noyes infoGPU vRAM or System RAMnoyesyes
User concepts infoAccess controlfine grained access rights according to SQL-standardAccess rights for users and roles on table levelyes infousing Azure authenticationyesfine grained access rights according to SQL-standard

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More resources
EsgynDBKineticaMicrosoft Azure AI SearchSolrYaacomo
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