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DBMS > Apache Phoenix vs. Google Cloud Firestore vs. GridDB vs. Tkrzw

System Properties Comparison Apache Phoenix vs. Google Cloud Firestore vs. GridDB vs. Tkrzw

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Editorial information provided by DB-Engines
NameApache Phoenix  Xexclude from comparisonGoogle Cloud Firestore  Xexclude from comparisonGridDB  Xexclude from comparisonTkrzw infoSuccessor of Tokyo Cabinet and Kyoto Cabinet  Xexclude from comparison
DescriptionA scale-out RDBMS with evolutionary schema built on Apache HBaseCloud Firestore is an auto-scaling document database for storing, syncing, and querying data for mobile and web apps. It offers seamless integration with other Firebase and Google Cloud Platform products.Scalable in-memory time series database optimized for IoT and Big 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 storeTime Series DBMSKey-value store
Secondary database modelsKey-value store
Relational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.97
Rank#126  Overall
#59  Relational DBMS
Score7.85
Rank#51  Overall
#8  Document stores
Score1.95
Rank#128  Overall
#10  Time Series DBMS
Score0.00
Rank#383  Overall
#60  Key-value stores
Websitephoenix.apache.orgfirebase.google.com/­products/­firestoregriddb.netdbmx.net/­tkrzw
Technical documentationphoenix.apache.orgfirebase.google.com/­docs/­firestoredocs.griddb.net
DeveloperApache Software FoundationGoogleToshiba CorporationMikio Hirabayashi
Initial release2014201720132020
Current release5.0-HBase2, July 2018 and 4.15-HBase1, December 20195.1, 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 availableOpen Source infoApache Version 2.0
Cloud-based only infoOnly available as a cloud servicenoyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaC++C++
Server operating systemsLinux
Unix
Windows
hostedLinuxLinux
macOS
Data schemeyes infolate-bound, schema-on-read capabilitiesschema-freeyesschema-free
Typing infopredefined data types such as float or dateyesyesyes infonumerical, string, blob, geometry, boolean, timestampno
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.nononono
Secondary indexesyesyesyes
SQL infoSupport of SQLyesnoSQL92, SQL-like TQL (Toshiba Query Language)no
APIs and other access methodsJDBCAndroid
gRPC (using protocol buffers) API
iOS
JavaScript API
RESTful HTTP API
JDBC
ODBC
Proprietary protocol
RESTful HTTP/JSON API
Supported programming languagesC
C#
C++
Go
Groovy
Java
PHP
Python
Scala
Go
Java
JavaScript
JavaScript (Node.js)
Objective-C
Python
C
C++
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
Ruby
C++
Java
Python
Ruby
Server-side scripts infoStored proceduresuser defined functionsyes, Firebase Rules & Cloud Functionsnono
Triggersnoyes, with Cloud Functionsyesno
Partitioning methods infoMethods for storing different data on different nodesShardingShardingShardingnone
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication
Source-replica replication
Multi-source replicationSource-replica replicationnone
MapReduce infoOffers an API for user-defined Map/Reduce methodsHadoop integrationUsing Cloud DataflowConnector for using GridDB as an input source and output destination for Hadoop MapReduce jobsno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate Consistency or Eventual ConsistencyImmediate ConsistencyImmediate consistency within container, eventual consistency across containersImmediate Consistency
Foreign keys infoReferential integritynononono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDyesACID at container level
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.yesyesyes infousing specific database classes
User concepts infoAccess controlAccess Control Lists (using HBase ACL) for RBAC, integration with Apache Ranger for RBAC & ABAC, multi-tenancyAccess rights for users, groups and roles based on Google Cloud Identity and Access Management. Security Rules for 3rd party authentication using Firebase Auth.Access rights for users can be defined per databaseno
More information provided by the system vendor
Apache PhoenixGoogle Cloud FirestoreGridDBTkrzw 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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More resources
Apache PhoenixGoogle Cloud FirestoreGridDBTkrzw infoSuccessor of Tokyo Cabinet and Kyoto Cabinet
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