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DBMS > Apache Pinot vs. Fauna vs. GridDB vs. Snowflake vs. Tkrzw

System Properties Comparison Apache Pinot vs. Fauna vs. GridDB vs. Snowflake vs. Tkrzw

Editorial information provided by DB-Engines
NameApache Pinot  Xexclude from comparisonFauna infopreviously named FaunaDB  Xexclude from comparisonGridDB  Xexclude from comparisonSnowflake  Xexclude from comparisonTkrzw infoSuccessor of Tokyo Cabinet and Kyoto Cabinet  Xexclude from comparison
DescriptionRealtime distributed OLAP datastore, designed to answer OLAP queries with low latencyFauna 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 DataCloud-based data warehousing service for structured and semi-structured dataA 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 modelRelational DBMSDocument store
Graph DBMS
Relational DBMS
Time Series DBMS
Time Series DBMSRelational DBMSKey-value store
Secondary database modelsKey-value store
Relational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.38
Rank#275  Overall
#126  Relational DBMS
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
Score130.36
Rank#8  Overall
#5  Relational DBMS
Score0.07
Rank#372  Overall
#57  Key-value stores
Websitepinot.apache.orgfauna.comgriddb.netwww.snowflake.comdbmx.net/­tkrzw
Technical documentationdocs.pinot.apache.orgdocs.fauna.comdocs.griddb.netdocs.snowflake.net/­manuals/­index.html
DeveloperApache Software Foundation and contributorsFauna, Inc.Toshiba CorporationSnowflake Computing Inc.Mikio Hirabayashi
Initial release20152014201320142020
Current release1.0.0, September 20235.1, August 20220.9.3, August 2020
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 availablecommercialOpen Source infoApache Version 2.0
Cloud-based only infoOnly available as a cloud servicenoyesnoyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageJavaScalaC++C++
Server operating systemsAll OS with a Java JDK11 or higherhostedLinuxhostedLinux
macOS
Data schemeyesschema-freeyesyes infosupport of semi-structured data formats (JSON, XML, Avro)schema-free
Typing infopredefined data types such as float or dateyesnoyes infonumerical, string, blob, geometry, boolean, timestampyesno
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 indexesyesyes
SQL infoSupport of SQLSQL-like query languagenoSQL92, SQL-like TQL (Toshiba Query Language)yesno
APIs and other access methodsJDBCRESTful HTTP APIJDBC
ODBC
Proprietary protocol
RESTful HTTP/JSON API
CLI Client
JDBC
ODBC
Supported programming languagesGo
Java
Python
C#
Go
Java
JavaScript
Python
Ruby
Scala
Swift
C
C++
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
Ruby
JavaScript (Node.js)
Python
C++
Java
Python
Ruby
Server-side scripts infoStored proceduresuser defined functionsnouser defined functionsno
Triggersnoyesno infosimilar concept for controling cloud resourcesno
Partitioning methods infoMethods for storing different data on different nodeshorizontal partitioninghorizontal partitioning infoconsistent hashingShardingyesnone
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replicationSource-replica replicationyesnone
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoConnector for using GridDB as an input source and output destination for Hadoop MapReduce jobsnono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate consistency within container, eventual consistency across containersImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integrityyesnoyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACID at container levelACID
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.noyesnoyes infousing specific database classes
User concepts infoAccess controlIdentity management, authentication, and access controlAccess rights for users can be defined per databaseUsers with fine-grained authorization concept, user roles and pluggable authenticationno
More information provided by the system vendor
Apache PinotFauna infopreviously named FaunaDBGridDBSnowflakeTkrzw 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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and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.

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More resources
Apache PinotFauna infopreviously named FaunaDBGridDBSnowflakeTkrzw infoSuccessor of Tokyo Cabinet and Kyoto Cabinet
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