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DBMS > Apache Pinot vs. EsgynDB vs. GridDB vs. LMDB

System Properties Comparison Apache Pinot vs. EsgynDB vs. GridDB vs. LMDB

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Editorial information provided by DB-Engines
NameApache Pinot  Xexclude from comparisonEsgynDB  Xexclude from comparisonGridDB  Xexclude from comparisonLMDB  Xexclude from comparison
DescriptionRealtime distributed OLAP datastore, designed to answer OLAP queries with low latencyEnterprise-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 library
Primary database modelRelational DBMSRelational DBMSTime Series DBMSKey-value store
Secondary database modelsKey-value store
Relational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.40
Rank#270  Overall
#125  Relational DBMS
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
Websitepinot.apache.orgwww.esgyn.cngriddb.netwww.symas.com/­symas-embedded-database-lmdb
Technical documentationdocs.pinot.apache.orgdocs.griddb.netwww.lmdb.tech/­doc
DeveloperApache Software Foundation and contributorsEsgynToshiba CorporationSymas
Initial release2015201520132011
Current release1.0.0, September 20235.1, August 20220.9.32, January 2024
License infoCommercial or Open SourceOpen Source infoApache Version 2.0commercialOpen Source infoAGPL version 3 and Apache License, version 2.0 , commercial license (standard and advanced editions) also availableOpen Source
Cloud-based only infoOnly available as a cloud servicenononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaC++, JavaC++C
Server operating systemsAll OS with a Java JDK11 or higherLinuxLinuxLinux
Unix
Windows
Data schemeyesyesyesschema-free
Typing infopredefined data types such as float or dateyesyesyes infonumerical, string, blob, geometry, boolean, timestamp
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.nonono
Secondary indexesyesyesno
SQL infoSupport of SQLSQL-like query languageyesSQL92, SQL-like TQL (Toshiba Query Language)no
APIs and other access methodsJDBCADO.NET
JDBC
ODBC
JDBC
ODBC
Proprietary protocol
RESTful HTTP/JSON API
Supported programming languagesGo
Java
Python
All 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
Server-side scripts infoStored proceduresJava Stored Proceduresnono
Triggersnoyesno
Partitioning methods infoMethods for storing different data on different nodeshorizontal partitioningShardingShardingnone
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication between multi datacentersSource-replica replicationnone
MapReduce infoOffers an API for user-defined Map/Reduce methodsyesConnector for using GridDB as an input source and output destination for Hadoop MapReduce jobsno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate consistency within container, eventual consistency across containersImmediate Consistency
Foreign keys infoReferential integrityyesnono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACID at container levelACID
Concurrency infoSupport for concurrent manipulation of datayesyesyes
Durability infoSupport for making data persistentyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyesyes
User concepts infoAccess controlfine grained access rights according to SQL-standardAccess rights for users can be defined per databaseno
More information provided by the system vendor
Apache PinotEsgynDBGridDBLMDB
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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and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.

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More resources
Apache PinotEsgynDBGridDBLMDB
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