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DBMS > Google Cloud Datastore vs. HBase vs. Prometheus vs. Riak KV

System Properties Comparison Google Cloud Datastore vs. HBase vs. Prometheus vs. Riak KV

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Editorial information provided by DB-Engines
NameGoogle Cloud Datastore  Xexclude from comparisonHBase  Xexclude from comparisonPrometheus  Xexclude from comparisonRiak KV  Xexclude from comparison
DescriptionAutomatically scaling NoSQL Database as a Service (DBaaS) on the Google Cloud PlatformWide-column store based on Apache Hadoop and on concepts of BigTableOpen-source Time Series DBMS and monitoring systemDistributed, fault tolerant key-value store
Primary database modelDocument storeWide column storeTime Series DBMSKey-value store infowith links between data sets and object tags for the creation of secondary indexes
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score4.47
Rank#76  Overall
#12  Document stores
Score30.50
Rank#26  Overall
#2  Wide column stores
Score8.42
Rank#47  Overall
#2  Time Series DBMS
Score4.10
Rank#82  Overall
#9  Key-value stores
Websitecloud.google.com/­datastorehbase.apache.orgprometheus.io
Technical documentationcloud.google.com/­datastore/­docshbase.apache.org/­book.htmlprometheus.io/­docswww.tiot.jp/­riak-docs/­riak/­kv/­latest
DeveloperGoogleApache Software Foundation infoApache top-level project, originally developed by PowersetOpenSource, formerly Basho Technologies
Initial release2008200820152009
Current release2.3.4, January 20213.2.0, December 2022
License infoCommercial or Open SourcecommercialOpen Source infoApache version 2Open Source infoApache 2.0Open Source infoApache version 2, commercial enterprise edition
Cloud-based only infoOnly available as a cloud serviceyesnonono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageJavaGoErlang
Server operating systemshostedLinux
Unix
Windows infousing Cygwin
Linux
Windows
Linux
OS X
Data schemeschema-freeschema-free, schema definition possibleyesschema-free
Typing infopredefined data types such as float or dateyes, details hereoptions to bring your own types, AVRONumeric data onlyno
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 infoImport of XML data possibleno
Secondary indexesyesnonorestricted
SQL infoSupport of SQLSQL-like query language (GQL)nonono
APIs and other access methodsgRPC (using protocol buffers) API
RESTful HTTP/JSON API
Java API
RESTful HTTP API
Thrift
RESTful HTTP/JSON APIHTTP API
Native Erlang Interface
Supported programming languages.Net
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
C
C#
C++
Groovy
Java
PHP
Python
Scala
.Net
C++
Go
Haskell
Java
JavaScript (Node.js)
Python
Ruby
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
Server-side scripts infoStored proceduresusing Google App Engineyes infoCoprocessors in JavanoErlang
TriggersCallbacks using the Google Apps Engineyesnoyes infopre-commit hooks and post-commit hooks
Partitioning methods infoMethods for storing different data on different nodesShardingShardingShardingSharding infono "single point of failure"
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication using PaxosMulti-source replication
Source-replica replication
yes infoby Federationselectable replication factor
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes infousing Google Cloud Dataflowyesnoyes
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate Consistency or Eventual Consistency depending on type of query and configuration infoStrong Consistency is default for entity lookups and queries within an Entity Group (but can instead be made eventually consistent). Other queries are always eventual consistent.Immediate Consistency or Eventual ConsistencynoneEventual Consistency
Foreign keys infoReferential integrityyes infovia ReferenceProperties or Ancestor pathsnonono infolinks between data sets can be stored
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACID infoSerializable Isolation within Transactions, Read Committed outside of TransactionsSingle row ACID (across millions of columns)nono
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.noyesno
User concepts infoAccess controlAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)Access Control Lists (ACL) for RBAC, integration with Apache Ranger for RBAC & ABACnoyes, using Riak Security

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More resources
Google Cloud DatastoreHBasePrometheusRiak KV
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