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

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

Editorial information provided by DB-Engines
NameGoogle Cloud Datastore  Xexclude from comparisonHBase  Xexclude from comparisonKinetica  Xexclude from comparisonLovefield  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 BigTableFully vectorized database across both GPUs and CPUsEmbeddable relational database for web apps written in pure JavaScriptDBMS 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
Score0.64
Rank#236  Overall
#109  Relational DBMS
Score0.29
Rank#293  Overall
#133  Relational DBMS
Score0.00
Rank#383  Overall
#7  Native XML DBMS
#25  Search engines
Websitecloud.google.com/­datastorehbase.apache.orgwww.kinetica.comgoogle.github.io/­lovefieldwww.searchxml.net/­category/­products
Technical documentationcloud.google.com/­datastore/­docshbase.apache.org/­book.htmldocs.kinetica.comgithub.com/­google/­lovefield/­blob/­master/­docs/­spec_index.mdwww.searchxml.net/­support/­handouts
DeveloperGoogleApache Software Foundation infoApache top-level project, originally developed by PowersetKineticaGoogleinformationpartners gmbh
Initial release20082008201220142015
Current release2.3.4, January 20217.1, August 20212.1.12, February 20171.0
License infoCommercial or Open SourcecommercialOpen Source infoApache version 2commercialOpen Source infoApache 2.0commercial
Cloud-based only infoOnly available as a cloud serviceyesnononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaC, C++JavaScriptC++
Server operating systemshostedLinux
Unix
Windows infousing Cygwin
Linuxserver-less, requires a JavaScript environment (browser, Node.js) infotested with Chrome, Firefox, IE, SafariWindows
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.nonononoyes
Secondary indexesyesnoyesyesyes
SQL infoSupport of SQLSQL-like query language (GQL)noSQL-like DML and DDL statementsSQL-like query language infovia JavaScript builder patternno
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
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
JavaScriptC++ infomost other programming languages supported via APIs
Server-side scripts infoStored proceduresusing Google App Engineyes infoCoprocessors in Javauser defined functionsnoyes infoon the application server
TriggersCallbacks using the Google Apps Engineyesyes infotriggers when inserted values for one or more columns fall within a specified rangeUsing read-only observersno
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 replicationnoneyes infosychronisation to multiple collections
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 Consistency
Foreign keys infoReferential integrityyes infovia ReferenceProperties or Ancestor pathsnoyesyesno
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)noACIDmultiple readers, single writer
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
Durability infoSupport for making data persistentyesyesyesyes, by using IndexedDB or the cloud service Firebase Realtime Databaseyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyesyes infoGPU vRAM or System RAMyes infousing MemoryDBno
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 levelnoDomain, group and role-based access control at the document level and for application services

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More resources
Google Cloud DatastoreHBaseKineticaLovefieldsearchxml
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