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

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

Editorial information provided by DB-Engines
NameEsgynDB  Xexclude from comparisonGreptimeDB  Xexclude from comparisonKinetica  Xexclude from comparisonMaxDB infoformerly named Adabas-D  Xexclude from comparisonSolr  Xexclude from comparison
DescriptionEnterprise-class SQL-on-Hadoop solution, powered by Apache TrafodionAn open source Time Series DBMS built for increased scalability, high performance and efficiencyFully vectorized database across both GPUs and CPUsA robust and reliable RDBMS optimized to run all major SAP solutionsA widely used distributed, scalable search engine based on Apache Lucene
Primary database modelRelational DBMSTime Series DBMSRelational DBMSRelational 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
Score0.12
Rank#351  Overall
#34  Time Series DBMS
Score0.66
Rank#234  Overall
#107  Relational DBMS
Score2.26
Rank#114  Overall
#55  Relational DBMS
Score41.02
Rank#24  Overall
#3  Search engines
Websitewww.esgyn.cngreptime.comwww.kinetica.commaxdb.sap.comsolr.apache.org
Technical documentationdocs.greptime.comdocs.kinetica.commaxdb.sap.com/­documentationsolr.apache.org/­resources.html
DeveloperEsgynGreptime Inc.KineticaSAP, acquired from Software AG (Adabas-D) in 1997Apache Software Foundation
Initial release20152022201219842006
Current release7.1, August 20217.9.10.12, February 20249.6.1, May 2024
License infoCommercial or Open SourcecommercialOpen Source infoApache Version 2.0commercialcommercial infoLimited community edition freeOpen 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.
Implementation languageC++, JavaRustC, C++C++Java
Server operating systemsLinuxAndroid
Docker
FreeBSD
Linux
macOS
Windows
LinuxAIX
HP-UX
Linux
Solaris
Windows
All OS with a Java VM inforuns as a servlet in servlet container (e.g. Tomcat, Jetty is included)
Data schemeyesschema-free, schema definition possibleyesyesyes infoDynamic Fields enables on-the-fly addition of new fields
Typing infopredefined data types such as float or dateyesyesyesyesyes 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 indexesyesyesyesyesyes infoAll search fields are automatically indexed
SQL infoSupport of SQLyesyesSQL-like DML and DDL statementsyesSolr Parallel SQL Interface
APIs and other access methodsADO.NET
JDBC
ODBC
gRPC
HTTP API
JDBC
JDBC
ODBC
RESTful HTTP API
ADO.NET
JDBC
ODBC
WebDAV
Java API
RESTful HTTP/JSON API
Supported programming languagesAll languages supporting JDBC/ODBC/ADO.NetC++
Erlang
Go
Java
JavaScript
C++
Java
JavaScript (Node.js)
Python
.Net
C#
Java
Perl
PHP
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 ProceduresPythonuser defined functionsyesJava plugins
Triggersnoyes infotriggers when inserted values for one or more columns fall within a specified rangeyesyes infoUser configurable commands triggered on index changes
Partitioning methods infoMethods for storing different data on different nodesShardingShardingShardingnoneSharding
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 ConsistencyImmediate Consistency or Eventual Consistency depending on configurationImmediate ConsistencyEventual Consistency
Foreign keys infoReferential integrityyesyesyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDnoACIDoptimistic 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 RAMnoyes
User concepts infoAccess controlfine grained access rights according to SQL-standardSimple rights management via user accountsAccess rights for users and roles on table levelfine grained access rights according to SQL-standardyes
More information provided by the system vendor
EsgynDBGreptimeDBKineticaMaxDB infoformerly named Adabas-DSolr
Specific characteristicsGreptimeDB is a SQL & Python-enabled timeseries database system built from scratch...
» more
Competitive advantages- Inherits advantages of Rust, such as excellent performance, memory safe, resource...
» more
Typical application scenariosFor IoT industries, GreptimeDB can seamless integrate with message queues and other...
» more
Key customersGreptime's clients span multiple sectors including IoT, connected vehicles, and energy...
» more
Market metricsGreptimeDB has garnered global recognition by topping GitHub trends following its...
» more
Licensing and pricing modelsGreptimeDB: open source, distributed, cloud-native TSDB; supports Hybrid Time-series...
» more

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EsgynDBGreptimeDBKineticaMaxDB infoformerly named Adabas-DSolr
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