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DBMS > Google Cloud Datastore vs. Greenplum vs. HBase vs. Kinetica

System Properties Comparison Google Cloud Datastore vs. Greenplum vs. HBase vs. Kinetica

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Editorial information provided by DB-Engines
NameGoogle Cloud Datastore  Xexclude from comparisonGreenplum  Xexclude from comparisonHBase  Xexclude from comparisonKinetica  Xexclude from comparison
DescriptionAutomatically scaling NoSQL Database as a Service (DBaaS) on the Google Cloud PlatformAnalytic Database platform built on PostgreSQL. Full name is Pivotal Greenplum Database infoA logical database in Greenplum is an array of individual PostgreSQL databases working together to present a single database image.Wide-column store based on Apache Hadoop and on concepts of BigTableFully vectorized database across both GPUs and CPUs
Primary database modelDocument storeRelational DBMSWide column storeRelational DBMS
Secondary database modelsDocument store
Spatial DBMS
Spatial 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
Score8.37
Rank#48  Overall
#30  Relational DBMS
Score30.50
Rank#26  Overall
#2  Wide column stores
Score0.64
Rank#236  Overall
#109  Relational DBMS
Websitecloud.google.com/­datastoregreenplum.orghbase.apache.orgwww.kinetica.com
Technical documentationcloud.google.com/­datastore/­docsdocs.greenplum.orghbase.apache.org/­book.htmldocs.kinetica.com
DeveloperGooglePivotal Software Inc.Apache Software Foundation infoApache top-level project, originally developed by PowersetKinetica
Initial release2008200520082012
Current release7.0.0, September 20232.3.4, January 20217.1, August 2021
License infoCommercial or Open SourcecommercialOpen Source infoApache 2.0Open Source infoApache version 2commercial
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 languageJavaC, C++
Server operating systemshostedLinuxLinux
Unix
Windows infousing Cygwin
Linux
Data schemeschema-freeyesschema-free, schema definition possibleyes
Typing infopredefined data types such as float or dateyes, details hereyesoptions to bring your own types, AVROyes
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.noyes infosince Version 4.2nono
Secondary indexesyesyesnoyes
SQL infoSupport of SQLSQL-like query language (GQL)yesnoSQL-like DML and DDL statements
APIs and other access methodsgRPC (using protocol buffers) API
RESTful HTTP/JSON API
JDBC
ODBC
Java API
RESTful HTTP API
Thrift
JDBC
ODBC
RESTful HTTP API
Supported programming languages.Net
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
C
Java
Perl
Python
R
C
C#
C++
Groovy
Java
PHP
Python
Scala
C++
Java
JavaScript (Node.js)
Python
Server-side scripts infoStored proceduresusing Google App Engineyesyes infoCoprocessors in Javauser defined functions
TriggersCallbacks using the Google Apps Engineyesyesyes infotriggers when inserted values for one or more columns fall within a specified range
Partitioning methods infoMethods for storing different data on different nodesShardingShardingShardingSharding
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication using PaxosSource-replica replicationMulti-source replication
Source-replica replication
Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes infousing Google Cloud Dataflowyesyesno
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 ConsistencyImmediate Consistency or Eventual ConsistencyImmediate Consistency or Eventual Consistency depending on configuration
Foreign keys infoReferential integrityyes infovia ReferenceProperties or Ancestor pathsyesnoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACID infoSerializable Isolation within Transactions, Read Committed outside of TransactionsACIDSingle row ACID (across millions of columns)no
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.nonoyesyes infoGPU vRAM or System RAM
User concepts infoAccess controlAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)fine grained access rights according to SQL-standardAccess Control Lists (ACL) for RBAC, integration with Apache Ranger for RBAC & ABACAccess rights for users and roles on table level

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More resources
Google Cloud DatastoreGreenplumHBaseKinetica
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