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DBMS > Google Cloud Firestore vs. HBase vs. Riak KV vs. TimescaleDB

System Properties Comparison Google Cloud Firestore vs. HBase vs. Riak KV vs. TimescaleDB

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Editorial information provided by DB-Engines
NameGoogle Cloud Firestore  Xexclude from comparisonHBase  Xexclude from comparisonRiak KV  Xexclude from comparisonTimescaleDB  Xexclude from comparison
DescriptionCloud 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.Wide-column store based on Apache Hadoop and on concepts of BigTableDistributed, fault tolerant key-value storeA time series DBMS optimized for fast ingest and complex queries, based on PostgreSQL
Primary database modelDocument storeWide column storeKey-value store infowith links between data sets and object tags for the creation of secondary indexesTime Series DBMS
Secondary database modelsRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score7.85
Rank#51  Overall
#8  Document stores
Score30.50
Rank#26  Overall
#2  Wide column stores
Score4.10
Rank#82  Overall
#9  Key-value stores
Score4.64
Rank#71  Overall
#4  Time Series DBMS
Websitefirebase.google.com/­products/­firestorehbase.apache.orgwww.timescale.com
Technical documentationfirebase.google.com/­docs/­firestorehbase.apache.org/­book.htmlwww.tiot.jp/­riak-docs/­riak/­kv/­latestdocs.timescale.com
DeveloperGoogleApache Software Foundation infoApache top-level project, originally developed by PowersetOpenSource, formerly Basho TechnologiesTimescale
Initial release2017200820092017
Current release2.3.4, January 20213.2.0, December 20222.13.0, November 2023
License infoCommercial or Open SourcecommercialOpen Source infoApache version 2Open Source infoApache version 2, commercial enterprise editionOpen Source infoApache 2.0
Cloud-based only infoOnly available as a cloud serviceyesnonono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaErlangC
Server operating systemshostedLinux
Unix
Windows infousing Cygwin
Linux
OS X
Linux
OS X
Windows
Data schemeschema-freeschema-free, schema definition possibleschema-freeyes
Typing infopredefined data types such as float or dateyesoptions to bring your own types, AVROnonumerics, strings, booleans, arrays, JSON blobs, geospatial dimensions, currencies, binary data, other complex data types
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.nononoyes
Secondary indexesyesnorestrictedyes
SQL infoSupport of SQLnononoyes infofull PostgreSQL SQL syntax
APIs and other access methodsAndroid
gRPC (using protocol buffers) API
iOS
JavaScript API
RESTful HTTP API
Java API
RESTful HTTP API
Thrift
HTTP API
Native Erlang Interface
ADO.NET
JDBC
native C library
ODBC
streaming API for large objects
Supported programming languagesGo
Java
JavaScript
JavaScript (Node.js)
Objective-C
Python
C
C#
C++
Groovy
Java
PHP
Python
Scala
C infounofficial client library
C#
C++ infounofficial client library
Clojure infounofficial client library
Dart infounofficial client library
Erlang
Go infounofficial client library
Groovy infounofficial client library
Haskell infounofficial client library
Java
JavaScript infounofficial client library
Lisp infounofficial client library
Perl infounofficial client library
PHP
Python
Ruby
Scala infounofficial client library
Smalltalk infounofficial client library
.Net
C
C++
Delphi
Java infoJDBC
JavaScript
Perl
PHP
Python
R
Ruby
Scheme
Tcl
Server-side scripts infoStored proceduresyes, Firebase Rules & Cloud Functionsyes infoCoprocessors in JavaErlanguser defined functions, PL/pgSQL, PL/Tcl, PL/Perl, PL/Python, PL/Java, PL/PHP, PL/R, PL/Ruby, PL/Scheme, PL/Unix shell
Triggersyes, with Cloud Functionsyesyes infopre-commit hooks and post-commit hooksyes
Partitioning methods infoMethods for storing different data on different nodesShardingShardingSharding infono "single point of failure"yes, across time and space (hash partitioning) attributes
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replicationMulti-source replication
Source-replica replication
selectable replication factorSource-replica replication with hot standby and reads on replicas info
MapReduce infoOffers an API for user-defined Map/Reduce methodsUsing Cloud Dataflowyesyesno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate Consistency or Eventual ConsistencyEventual ConsistencyImmediate Consistency
Foreign keys infoReferential integritynonono infolinks between data sets can be storedyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datayesSingle row ACID (across millions of columns)noACID
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.yesno
User concepts infoAccess controlAccess rights for users, groups and roles based on Google Cloud Identity and Access Management. Security Rules for 3rd party authentication using Firebase Auth.Access Control Lists (ACL) for RBAC, integration with Apache Ranger for RBAC & ABACyes, using Riak Securityfine grained access rights according to SQL-standard

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More resources
Google Cloud FirestoreHBaseRiak KVTimescaleDB
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