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DBMS > Google Cloud Datastore vs. HBase vs. Kinetica vs. searchxml vs. SQL.JS

System Properties Comparison Google Cloud Datastore vs. HBase vs. Kinetica vs. searchxml vs. SQL.JS

Editorial information provided by DB-Engines
NameGoogle Cloud Datastore  Xexclude from comparisonHBase  Xexclude from comparisonKinetica  Xexclude from comparisonsearchxml  Xexclude from comparisonSQL.JS  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 BigTableFully vectorized database across both GPUs and CPUsDBMS for structured and unstructured content wrapped with an application serverPort of SQLite to JavaScript
Primary database modelDocument storeWide column storeRelational DBMSNative XML DBMS
Search engine
Relational DBMS
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
Score0.64
Rank#236  Overall
#109  Relational DBMS
Score0.00
Rank#383  Overall
#7  Native XML DBMS
#25  Search engines
Score0.53
Rank#252  Overall
#116  Relational DBMS
Websitecloud.google.com/­datastorehbase.apache.orgwww.kinetica.comwww.searchxml.net/­category/­productssql.js.org
Technical documentationcloud.google.com/­datastore/­docshbase.apache.org/­book.htmldocs.kinetica.comwww.searchxml.net/­support/­handoutssql.js.org/­documentation/­index.html
DeveloperGoogleApache Software Foundation infoApache top-level project, originally developed by PowersetKineticainformationpartners gmbhAlon Zakai infoenhancements implemented by others
Initial release20082008201220152012
Current release2.3.4, January 20217.1, August 20211.0
License infoCommercial or Open SourcecommercialOpen Source infoApache version 2commercialcommercialOpen Source
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 languageJavaC, C++C++JavaScript
Server operating systemshostedLinux
Unix
Windows infousing Cygwin
LinuxWindowsserver-less, requires a JavaScript environment (browser, Node.js)
Data schemeschema-freeschema-free, schema definition possibleyesschema-freeyes
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.nononoyesno
Secondary indexesyesnoyesyes
SQL infoSupport of SQLSQL-like query language (GQL)noSQL-like DML and DDL statementsnoyes infoSQL-92 is not fully supported
APIs and other access methodsgRPC (using protocol buffers) API
RESTful HTTP/JSON API
Java API
RESTful HTTP API
Thrift
JDBC
ODBC
RESTful HTTP API
RESTful HTTP API
WebDAV
XQuery
XSLT
JavaScript API
Supported programming languages.Net
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
C
C#
C++
Groovy
Java
PHP
Python
Scala
C++
Java
JavaScript (Node.js)
Python
C++ infomost other programming languages supported via APIsJavaScript
Server-side scripts infoStored proceduresusing Google App Engineyes infoCoprocessors in Javauser defined functionsyes infoon the application serverno
TriggersCallbacks using the Google Apps Engineyesyes infotriggers when inserted values for one or more columns fall within a specified rangenono
Partitioning methods infoMethods for storing different data on different nodesShardingShardingShardingnonenone
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication using PaxosMulti-source replication
Source-replica replication
Source-replica replicationyes infosychronisation to multiple collectionsnone
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes infousing Google Cloud Dataflowyesnonono
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 ConsistencyImmediate Consistency or Eventual Consistency depending on configurationImmediate Consistencynone
Foreign keys infoReferential integrityyes infovia ReferenceProperties or Ancestor pathsnoyesnoyes
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)nomultiple readers, single writerACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyesyesyesno infoexcept by serializing a db to a file
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyesyes infoGPU vRAM or System RAMnoyes
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 and roles on table levelDomain, group and role-based access control at the document level and for application servicesno

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More resources
Google Cloud DatastoreHBaseKineticasearchxmlSQL.JS
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