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DBMS > Fauna vs. GridDB vs. Heroic vs. SpatiaLite vs. Tkrzw

System Properties Comparison Fauna vs. GridDB vs. Heroic vs. SpatiaLite vs. Tkrzw

Editorial information provided by DB-Engines
NameFauna infopreviously named FaunaDB  Xexclude from comparisonGridDB  Xexclude from comparisonHeroic  Xexclude from comparisonSpatiaLite  Xexclude from comparisonTkrzw infoSuccessor of Tokyo Cabinet and Kyoto Cabinet  Xexclude from comparison
DescriptionFauna provides a web-native interface, with support for GraphQL and custom business logic that integrates seamlessly with the rest of the serverless ecosystem. The underlying globally distributed storage and compute platform is fast, consistent, and reliable, with a modern security infrastructure.Scalable in-memory time series database optimized for IoT and Big DataTime Series DBMS built at Spotify based on Cassandra or Google Cloud Bigtable, and ElasticSearchSpatial extension of SQLiteA concept of libraries, allowing an application program to store and query key-value pairs in a file. Successor of Tokyo Cabinet and Kyoto Cabinet
Primary database modelDocument store
Graph DBMS
Relational DBMS
Time Series DBMS
Time Series DBMSTime Series DBMSSpatial DBMSKey-value store
Secondary database modelsKey-value store
Relational DBMS
Relational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.55
Rank#151  Overall
#26  Document stores
#14  Graph DBMS
#71  Relational DBMS
#13  Time Series DBMS
Score2.09
Rank#120  Overall
#10  Time Series DBMS
Score0.46
Rank#265  Overall
#22  Time Series DBMS
Score1.63
Rank#146  Overall
#3  Spatial DBMS
Score0.07
Rank#372  Overall
#57  Key-value stores
Websitefauna.comgriddb.netgithub.com/­spotify/­heroicwww.gaia-gis.it/­fossil/­libspatialite/­indexdbmx.net/­tkrzw
Technical documentationdocs.fauna.comdocs.griddb.netspotify.github.io/­heroicwww.gaia-gis.it/­gaia-sins/­spatialite_topics.html
DeveloperFauna, Inc.Toshiba CorporationSpotifyAlessandro FurieriMikio Hirabayashi
Initial release20142013201420082020
Current release5.1, August 20225.0.0, August 20200.9.3, August 2020
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 2.0Open Source infoMPL 1.1, GPL v2.0 or LGPL v2.1Open Source infoApache Version 2.0
Cloud-based only infoOnly available as a cloud serviceyesnononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageScalaC++JavaC++C++
Server operating systemshostedLinuxserver-lessLinux
macOS
Data schemeschema-freeyesschema-freeyesschema-free
Typing infopredefined data types such as float or datenoyes infonumerical, string, blob, geometry, boolean, timestampyesyesno
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.nonononono
Secondary indexesyesyesyes infovia Elasticsearchyes
SQL infoSupport of SQLnoSQL92, SQL-like TQL (Toshiba Query Language)noyesno
APIs and other access methodsRESTful HTTP APIJDBC
ODBC
Proprietary protocol
RESTful HTTP/JSON API
HQL (Heroic Query Language, a JSON-based language)
HTTP API
Supported programming languagesC#
Go
Java
JavaScript
Python
Ruby
Scala
Swift
C
C++
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
Ruby
C++
Java
Python
Ruby
Server-side scripts infoStored proceduresuser defined functionsnononono
Triggersnoyesnoyesno
Partitioning methods infoMethods for storing different data on different nodeshorizontal partitioning infoconsistent hashingShardingShardingnonenone
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replicationSource-replica replicationyesnonenone
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoConnector for using GridDB as an input source and output destination for Hadoop MapReduce jobsnonono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate consistency within container, eventual consistency across containersEventual Consistency
Immediate Consistency
Immediate Consistency
Foreign keys infoReferential integrityyesnonoyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACID at container levelnoACID
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.noyesnoyesyes infousing specific database classes
User concepts infoAccess controlIdentity management, authentication, and access controlAccess rights for users can be defined per databasenono
More information provided by the system vendor
Fauna infopreviously named FaunaDBGridDBHeroicSpatiaLiteTkrzw infoSuccessor of Tokyo Cabinet and Kyoto Cabinet
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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Fauna infopreviously named FaunaDBGridDBHeroicSpatiaLiteTkrzw infoSuccessor of Tokyo Cabinet and Kyoto Cabinet
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