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DBMS > EsgynDB vs. GridDB vs. Solr vs. StarRocks

System Properties Comparison EsgynDB vs. GridDB vs. Solr vs. StarRocks

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Editorial information provided by DB-Engines
NameEsgynDB  Xexclude from comparisonGridDB  Xexclude from comparisonSolr  Xexclude from comparisonStarRocks  Xexclude from comparison
DescriptionEnterprise-class SQL-on-Hadoop solution, powered by Apache TrafodionScalable in-memory time series database optimized for IoT and Big DataA widely used distributed, scalable search engine based on Apache LuceneAn open source, high-performance columnar analytical database that enables real-time, multi-dimensional, and highly concurrent data analytics infoForked from Apache Doris
Primary database modelRelational DBMSTime Series DBMSSearch engineRelational DBMS
Secondary database modelsKey-value store
Relational DBMS
Spatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.25
Rank#312  Overall
#138  Relational DBMS
Score2.09
Rank#120  Overall
#10  Time Series DBMS
Score41.02
Rank#24  Overall
#3  Search engines
Score0.93
Rank#198  Overall
#93  Relational DBMS
Websitewww.esgyn.cngriddb.netsolr.apache.orgwww.starrocks.io
Technical documentationdocs.griddb.netsolr.apache.org/­resources.htmldocs.starrocks.io/­en-us/­latest/­introduction/­StarRocks_intro
DeveloperEsgynToshiba CorporationApache Software FoundationThe Linux Foundation infosince Feb 2023
Initial release2015201320062020
Current release5.1, August 20229.6.1, May 20242.5.3, March 2023
License infoCommercial or Open SourcecommercialOpen Source infoAGPL version 3 and Apache License, version 2.0 , commercial license (standard and advanced editions) also availableOpen Source infoApache Version 2Open Source infoApache Version 2.0
Cloud-based only infoOnly available as a cloud servicenononono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageC++, JavaC++JavaC++, Java
Server operating systemsLinuxLinuxAll OS with a Java VM inforuns as a servlet in servlet container (e.g. Tomcat, Jetty is included)Linux
Data schemeyesyesyes infoDynamic Fields enables on-the-fly addition of new fieldsyes
Typing infopredefined data types such as float or dateyesyes infonumerical, string, blob, geometry, boolean, timestampyes 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.nonoyesno
Secondary indexesyesyesyes infoAll search fields are automatically indexedyes
SQL infoSupport of SQLyesSQL92, SQL-like TQL (Toshiba Query Language)Solr Parallel SQL Interfaceyes
APIs and other access methodsADO.NET
JDBC
ODBC
JDBC
ODBC
Proprietary protocol
RESTful HTTP/JSON API
Java API
RESTful HTTP/JSON API
JDBC
MySQL protocol
Supported programming languagesAll languages supporting JDBC/ODBC/ADO.NetC
C++
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
Ruby
.Net
Erlang
Java
JavaScript
any language that supports sockets and either XML or JSON
Perl
PHP
Python
Ruby
Scala
Java
Server-side scripts infoStored proceduresJava Stored ProceduresnoJava pluginsuser defined functions
Triggersnoyesyes infoUser configurable commands triggered on index changesno
Partitioning methods infoMethods for storing different data on different nodesShardingShardingShardinghorizontal partitioning (by range and hash)
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication between multi datacentersSource-replica replicationyes
MapReduce infoOffers an API for user-defined Map/Reduce methodsyesConnector for using GridDB as an input source and output destination for Hadoop MapReduce jobsspark-solr: github.com/­lucidworks/­spark-solr and streaming expressions to reduceno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate consistency within container, eventual consistency across containersEventual ConsistencyImmediate Consistency
Foreign keys infoReferential integrityyesnonono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACID at container leveloptimistic lockingno
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.noyesyesno
User concepts infoAccess controlfine grained access rights according to SQL-standardAccess rights for users can be defined per databaseyesRole based access control and fine grained access rights
More information provided by the system vendor
EsgynDBGridDBSolrStarRocks
Specific characteristicsGridDB is a highly scalable, in-memory time series database optimized for IoT and...
» more
Competitive advantages1. Optimized for IoT Equipped with Toshiba's proprietary key-container data model...
» more
Typical application scenariosFactory IoT, Automative Industry, Energy, BEMS, Smart Community, Monitoring system.
» more
Key customersDenso International [see use case ] An Electric Power company [see use case ] Ishinomaki...
» more
Market metricsGitHub trending repository
» more
Licensing and pricing modelsOpen Source license (AGPL v3 & Apache v2) Commercial license (subscription)
» more

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EsgynDBGridDBSolrStarRocks
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