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DBMS > EsgynDB vs. Kinetica vs. MaxDB vs. Milvus vs. Solr

System Properties Comparison EsgynDB vs. Kinetica vs. MaxDB vs. Milvus vs. Solr

Editorial information provided by DB-Engines
NameEsgynDB  Xexclude from comparisonKinetica  Xexclude from comparisonMaxDB infoformerly named Adabas-D  Xexclude from comparisonMilvus  Xexclude from comparisonSolr  Xexclude from comparison
DescriptionEnterprise-class SQL-on-Hadoop solution, powered by Apache TrafodionFully vectorized database across both GPUs and CPUsA robust and reliable RDBMS optimized to run all major SAP solutionsA DBMS designed for efficient storage of vector data and vector similarity searchesA widely used distributed, scalable search engine based on Apache Lucene
Primary database modelRelational DBMSRelational DBMSRelational DBMSVector DBMSSearch engine
Secondary database modelsSpatial DBMS
Time Series DBMS
Spatial 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
Score2.26
Rank#114  Overall
#55  Relational DBMS
Score2.78
Rank#103  Overall
#4  Vector DBMS
Score41.02
Rank#24  Overall
#3  Search engines
Websitewww.esgyn.cnwww.kinetica.commaxdb.sap.commilvus.iosolr.apache.org
Technical documentationdocs.kinetica.commaxdb.sap.com/­documentationmilvus.io/­docs/­overview.mdsolr.apache.org/­resources.html
DeveloperEsgynKineticaSAP, acquired from Software AG (Adabas-D) in 1997Apache Software Foundation
Initial release20152012198420192006
Current release7.1, August 20217.9.10.12, February 20242.4.4, May 20249.6.1, May 2024
License infoCommercial or Open Sourcecommercialcommercialcommercial infoLimited community edition freeOpen Source infoApache Version 2.0Open Source infoApache Version 2
Cloud-based only infoOnly available as a cloud servicenonononono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Zilliz Cloud – Cloud-native service for Milvus
Implementation languageC++, JavaC, C++C++C++, GoJava
Server operating systemsLinuxLinuxAIX
HP-UX
Linux
Solaris
Windows
Linux
macOS info10.14 or later
Windows infowith WSL 2 enabled
All OS with a Java VM inforuns as a servlet in servlet container (e.g. Tomcat, Jetty is included)
Data schemeyesyesyesyes infoDynamic Fields enables on-the-fly addition of new fields
Typing infopredefined data types such as float or dateyesyesyesVector, Numeric and Stringyes infosupports customizable data types and automatic typing
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
Secondary indexesyesyesyesnoyes infoAll search fields are automatically indexed
SQL infoSupport of SQLyesSQL-like DML and DDL statementsyesnoSolr Parallel SQL Interface
APIs and other access methodsADO.NET
JDBC
ODBC
JDBC
ODBC
RESTful HTTP API
ADO.NET
JDBC
ODBC
WebDAV
RESTful HTTP APIJava API
RESTful HTTP/JSON API
Supported programming languagesAll languages supporting JDBC/ODBC/ADO.NetC++
Java
JavaScript (Node.js)
Python
.Net
C#
Java
Perl
PHP
Python
C++
Go
Java
JavaScript (Node.js)
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 functionsyesnoJava plugins
Triggersnoyes infotriggers when inserted values for one or more columns fall within a specified rangeyesnoyes infoUser configurable commands triggered on index changes
Partitioning methods infoMethods for storing different data on different nodesShardingShardingnoneShardingSharding
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication between multi datacentersSource-replica replicationSource-replica replicationyes
MapReduce infoOffers an API for user-defined Map/Reduce methodsyesnononospark-solr: github.com/­lucidworks/­spark-solr and streaming expressions to reduce
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate Consistency or Eventual Consistency depending on configurationImmediate ConsistencyBounded Staleness
Eventual Consistency
Immediate Consistency
Session Consistency
Tunable Consistency
Eventual Consistency
Foreign keys infoReferential integrityyesyesyesnono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDnoACIDnooptimistic locking
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 levelfine grained access rights according to SQL-standardRole based access control and fine grained access rightsyes
More information provided by the system vendor
EsgynDBKineticaMaxDB infoformerly named Adabas-DMilvusSolr
Specific characteristicsMilvus is an open-source and cloud-native vector database built for production-ready...
» more
Competitive advantagesHighly available, versatile, and robust with millisecond latency. Supports batch...
» more
Typical application scenariosRAG: retrieval augmented generation Video media : video understanding, video deduplication....
» more
Key customersMilvus is trusted by thousands of enterprises, including PayPal, eBay, IKEA, LINE,...
» more
Market metricsAs of January 2024, 25k+ GitHub stars 10M+ downloads and installations​ ​ 3k+ enterprise...
» more
Licensing and pricing modelsMilvus was released under the open-source Apache License 2.0 in October 2019. Fully-managed...
» more

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EsgynDBKineticaMaxDB infoformerly named Adabas-DMilvusSolr
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