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DBMS > EsgynDB vs. Firebolt vs. GridDB vs. LMDB

System Properties Comparison EsgynDB vs. Firebolt vs. GridDB vs. LMDB

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Editorial information provided by DB-Engines
NameEsgynDB  Xexclude from comparisonFirebolt  Xexclude from comparisonGridDB  Xexclude from comparisonLMDB  Xexclude from comparison
DescriptionEnterprise-class SQL-on-Hadoop solution, powered by Apache TrafodionHighly scalable cloud data warehouse and analytics product infoForked from ClickhouseScalable 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
Score0.16
Rank#329  Overall
#146  Relational DBMS
Score1.90
Rank#134  Overall
#62  Relational DBMS
Score1.95
Rank#128  Overall
#10  Time Series DBMS
Score1.99
Rank#125  Overall
#21  Key-value stores
Websitewww.esgyn.cnwww.firebolt.iogriddb.netwww.symas.com/­symas-embedded-database-lmdb
Technical documentationdocs.firebolt.iodocs.griddb.netwww.lmdb.tech/­doc
DeveloperEsgynFirebolt Analytics Inc.Toshiba CorporationSymas
Initial release2015202020132011
Current release5.1, August 20220.9.32, January 2024
License infoCommercial or Open SourcecommercialcommercialOpen 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 servicenoyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageC++, JavaC++C
Server operating systemsLinuxhostedLinuxLinux
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 indexesyesyesyesno
SQL infoSupport of SQLyesyesSQL92, SQL-like TQL (Toshiba Query Language)no
APIs and other access methodsADO.NET
JDBC
ODBC
.Net
ODBC
RESTful HTTP API
JDBC
ODBC
Proprietary protocol
RESTful HTTP/JSON API
Supported programming languagesAll languages supporting JDBC/ODBC/ADO.NetGo
JavaScript (Node.js)
Python
C
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 Proceduresnonono
Triggersnonoyesno
Partitioning methods infoMethods for storing different data on different nodesShardingShardingnone
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication between multi datacentersdepending on storage layerSource-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
EsgynDBFireboltGridDBLMDB
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
EsgynDBFireboltGridDBLMDB
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