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DBMS > Google Cloud Datastore vs. HBase vs. Hive vs. Kinetica vs. searchxml

System Properties Comparison Google Cloud Datastore vs. HBase vs. Hive vs. Kinetica vs. searchxml

Editorial information provided by DB-Engines
NameGoogle Cloud Datastore  Xexclude from comparisonHBase  Xexclude from comparisonHive  Xexclude from comparisonKinetica  Xexclude from comparisonsearchxml  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 BigTabledata warehouse software for querying and managing large distributed datasets, built on HadoopFully vectorized database across both GPUs and CPUsDBMS for structured and unstructured content wrapped with an application server
Primary database modelDocument storeWide column storeRelational DBMSRelational DBMSNative XML DBMS
Search engine
Secondary database modelsSpatial DBMS
Time Series DBMS
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
Score61.17
Rank#18  Overall
#12  Relational DBMS
Score0.64
Rank#236  Overall
#109  Relational DBMS
Score0.00
Rank#383  Overall
#7  Native XML DBMS
#25  Search engines
Websitecloud.google.com/­datastorehbase.apache.orghive.apache.orgwww.kinetica.comwww.searchxml.net/­category/­products
Technical documentationcloud.google.com/­datastore/­docshbase.apache.org/­book.htmlcwiki.apache.org/­confluence/­display/­Hive/­Homedocs.kinetica.comwww.searchxml.net/­support/­handouts
DeveloperGoogleApache Software Foundation infoApache top-level project, originally developed by PowersetApache Software Foundation infoinitially developed by FacebookKineticainformationpartners gmbh
Initial release20082008201220122015
Current release2.3.4, January 20213.1.3, April 20227.1, August 20211.0
License infoCommercial or Open SourcecommercialOpen Source infoApache version 2Open Source infoApache Version 2commercialcommercial
Cloud-based only infoOnly available as a cloud serviceyesnononono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageJavaJavaC, C++C++
Server operating systemshostedLinux
Unix
Windows infousing Cygwin
All OS with a Java VMLinuxWindows
Data schemeschema-freeschema-free, schema definition possibleyesyesschema-free
Typing infopredefined data types such as float or dateyes, details hereoptions to bring your own types, AVROyesyesyes
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 indexesyesnoyesyesyes
SQL infoSupport of SQLSQL-like query language (GQL)noSQL-like DML and DDL statementsSQL-like DML and DDL statementsno
APIs and other access methodsgRPC (using protocol buffers) API
RESTful HTTP/JSON API
Java API
RESTful HTTP API
Thrift
JDBC
ODBC
Thrift
JDBC
ODBC
RESTful HTTP API
RESTful HTTP API
WebDAV
XQuery
XSLT
Supported programming languages.Net
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
C
C#
C++
Groovy
Java
PHP
Python
Scala
C++
Java
PHP
Python
C++
Java
JavaScript (Node.js)
Python
C++ infomost other programming languages supported via APIs
Server-side scripts infoStored proceduresusing Google App Engineyes infoCoprocessors in Javayes infouser defined functions and integration of map-reduceuser defined functionsyes infoon the application server
TriggersCallbacks using the Google Apps Engineyesnoyes infotriggers when inserted values for one or more columns fall within a specified rangeno
Partitioning methods infoMethods for storing different data on different nodesShardingShardingShardingShardingnone
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication using PaxosMulti-source replication
Source-replica replication
selectable replication factorSource-replica replicationyes infosychronisation to multiple collections
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes infousing Google Cloud Dataflowyesyes infoquery execution via MapReducenono
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 ConsistencyEventual ConsistencyImmediate Consistency or Eventual Consistency depending on configurationImmediate Consistency
Foreign keys infoReferential integrityyes infovia ReferenceProperties or Ancestor pathsnonoyesno
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)nonomultiple readers, single writer
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.noyesyes infoGPU vRAM or System RAMno
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 & ABACAccess rights for users, groups and rolesAccess rights for users and roles on table levelDomain, group and role-based access control at the document level and for application services

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More resources
Google Cloud DatastoreHBaseHiveKineticasearchxml
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