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DBMS > Google Cloud Datastore vs. HBase vs. MonetDB vs. Postgres-XL

System Properties Comparison Google Cloud Datastore vs. HBase vs. MonetDB vs. Postgres-XL

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Editorial information provided by DB-Engines
NameGoogle Cloud Datastore  Xexclude from comparisonHBase  Xexclude from comparisonMonetDB  Xexclude from comparisonPostgres-XL  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 BigTableA relational database management system that stores data in columnsBased on PostgreSQL enhanced with MPP and write-scale-out cluster features
Primary database modelDocument storeWide column storeRelational DBMSRelational DBMS
Secondary database modelsDocument store
Spatial DBMS
Document store
Spatial 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
Score1.72
Rank#145  Overall
#67  Relational DBMS
Score0.49
Rank#256  Overall
#117  Relational DBMS
Websitecloud.google.com/­datastorehbase.apache.orgwww.monetdb.orgwww.postgres-xl.org
Technical documentationcloud.google.com/­datastore/­docshbase.apache.org/­book.htmlwww.monetdb.org/­Documentationwww.postgres-xl.org/­documentation
DeveloperGoogleApache Software Foundation infoApache top-level project, originally developed by PowersetMonetDB BV
Initial release2008200820042014 infosince 2012, originally named StormDB
Current release2.3.4, January 2021Dec2023 (11.49), December 202310 R1, October 2018
License infoCommercial or Open SourcecommercialOpen Source infoApache version 2Open Source infoMozilla Public License 2.0Open Source infoMozilla public license
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 languageJavaCC
Server operating systemshostedLinux
Unix
Windows infousing Cygwin
FreeBSD
Linux
OS X
Solaris
Windows
Linux
macOS
Data schemeschema-freeschema-free, schema definition possibleyesyes
Typing infopredefined data types such as float or dateyes, details hereoptions to bring your own types, AVROyesyes
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.nonoyes infoXML type, but no XML query functionality
Secondary indexesyesnoyesyes
SQL infoSupport of SQLSQL-like query language (GQL)noyes infoSQL 2003 with some extensionsyes infodistributed, parallel query execution
APIs and other access methodsgRPC (using protocol buffers) API
RESTful HTTP/JSON API
Java API
RESTful HTTP API
Thrift
JDBC
native C library infoMAPI library (MonetDB application programming interface)
ODBC
ADO.NET
JDBC
native C library
ODBC
streaming API for large objects
Supported programming languages.Net
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
C
C#
C++
Groovy
Java
PHP
Python
Scala
C
C++
Java
JavaScript (Node.js)
Perl
PHP
Python
R
Ruby
.Net
C
C++
Delphi
Erlang
Java
JavaScript (Node.js)
Perl
PHP
Python
Tcl
Server-side scripts infoStored proceduresusing Google App Engineyes infoCoprocessors in Javayes, in SQL, C, Ruser defined functions
TriggersCallbacks using the Google Apps Engineyesyesyes
Partitioning methods infoMethods for storing different data on different nodesShardingShardingSharding via remote tableshorizontal partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication using PaxosMulti-source replication
Source-replica replication
none infoSource-replica replication available in experimental status
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes infousing Google Cloud Dataflowyesnono
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
Foreign keys infoReferential integrityyes infovia ReferenceProperties or Ancestor pathsnoyesyes
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)ACIDACID infoMVCC
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 & ABACfine grained access rights according to SQL-standardfine grained access rights according to SQL-standard

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More resources
Google Cloud DatastoreHBaseMonetDBPostgres-XL
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