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DBMS > EsgynDB vs. GridDB vs. LMDB vs. Sadas Engine vs. Solr

System Properties Comparison EsgynDB vs. GridDB vs. LMDB vs. Sadas Engine vs. Solr

Editorial information provided by DB-Engines
NameEsgynDB  Xexclude from comparisonGridDB  Xexclude from comparisonLMDB  Xexclude from comparisonSadas Engine  Xexclude from comparisonSolr  Xexclude from comparison
DescriptionEnterprise-class SQL-on-Hadoop solution, powered by Apache TrafodionScalable in-memory time series database optimized for IoT and Big DataA high performant, light-weight, embedded key-value database librarySADAS Engine is a columnar DBMS specifically designed for high performance in data warehouse environmentsA widely used distributed, scalable search engine based on Apache Lucene
Primary database modelRelational DBMSTime Series DBMSKey-value storeRelational DBMSSearch engine
Secondary database modelsKey-value store
Relational DBMS
Spatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.16
Rank#329  Overall
#146  Relational DBMS
Score1.95
Rank#128  Overall
#10  Time Series DBMS
Score1.99
Rank#125  Overall
#21  Key-value stores
Score0.00
Rank#383  Overall
#158  Relational DBMS
Score42.91
Rank#24  Overall
#3  Search engines
Websitewww.esgyn.cngriddb.netwww.symas.com/­symas-embedded-database-lmdbwww.sadasengine.comsolr.apache.org
Technical documentationdocs.griddb.netwww.lmdb.tech/­docwww.sadasengine.com/­en/­sadas-engine-download-free-trial-and-documentation/­#documentationsolr.apache.org/­resources.html
DeveloperEsgynToshiba CorporationSymasSADAS s.r.l.Apache Software Foundation
Initial release20152013201120062006
Current release5.1, August 20220.9.32, January 20248.09.6.0, April 2024
License infoCommercial or Open SourcecommercialOpen Source infoAGPL version 3 and Apache License, version 2.0 , commercial license (standard and advanced editions) also availableOpen Sourcecommercial infofree trial version availableOpen 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++, JavaC++CC++Java
Server operating systemsLinuxLinuxLinux
Unix
Windows
AIX
Linux
Windows
All OS with a Java VM inforuns as a servlet in servlet container (e.g. Tomcat, Jetty is included)
Data schemeyesyesschema-freeyesyes infoDynamic Fields enables on-the-fly addition of new fields
Typing infopredefined data types such as float or dateyesyes infonumerical, string, blob, geometry, boolean, timestampyesyes 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 indexesyesyesnoyesyes infoAll search fields are automatically indexed
SQL infoSupport of SQLyesSQL92, SQL-like TQL (Toshiba Query Language)noyesSolr Parallel SQL Interface
APIs and other access methodsADO.NET
JDBC
ODBC
JDBC
ODBC
Proprietary protocol
RESTful HTTP/JSON API
JDBC
ODBC
Proprietary protocol
Java API
RESTful HTTP/JSON API
Supported programming languagesAll languages supporting JDBC/ODBC/ADO.NetC
C++
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
Ruby
.Net
C
C++
Clojure
Go
Haskell
Java
JavaScript (Node.js)
Lisp
Lua
MatLab
Nim
Objective C
OCaml
Perl
PHP
Python
R
Ruby
Rust
Swift
Tcl
.Net
C
C#
C++
Groovy
Java
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 ProceduresnononoJava plugins
Triggersnoyesnonoyes infoUser configurable commands triggered on index changes
Partitioning methods infoMethods for storing different data on different nodesShardingShardingnonehorizontal partitioningSharding
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication between multi datacentersSource-replica replicationnonenoneyes
MapReduce infoOffers an API for user-defined Map/Reduce methodsyesConnector for using GridDB as an input source and output destination for Hadoop MapReduce jobsnonospark-solr: github.com/­lucidworks/­spark-solr and streaming expressions to reduce
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate consistency within container, eventual consistency across containersImmediate ConsistencyImmediate ConsistencyEventual Consistency
Foreign keys infoReferential integrityyesnonoyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACID at container levelACIDoptimistic 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.noyesyesyes infomanaged by 'Learn by Usage'yes
User concepts infoAccess controlfine grained access rights according to SQL-standardAccess rights for users can be defined per databasenoAccess rights for users, groups and roles according to SQL-standardyes
More information provided by the system vendor
EsgynDBGridDBLMDBSadas EngineSolr
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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More resources
EsgynDBGridDBLMDBSadas EngineSolr
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