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DBMS > Google Cloud Datastore vs. Greenplum vs. OrigoDB vs. SiteWhere vs. Teradata Aster

System Properties Comparison Google Cloud Datastore vs. Greenplum vs. OrigoDB vs. SiteWhere vs. Teradata Aster

Editorial information provided by DB-Engines
NameGoogle Cloud Datastore  Xexclude from comparisonGreenplum  Xexclude from comparisonOrigoDB  Xexclude from comparisonSiteWhere  Xexclude from comparisonTeradata Aster  Xexclude from comparison
Teradata Aster has been integrated into other Teradata systems and therefore will be removed from the DB-Engines ranking.
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.A fully ACID in-memory object graph databaseM2M integration platform for persisting/querying time series dataPlatform for big data analytics on multistructured data sources and types
Primary database modelDocument storeRelational DBMSDocument store
Object oriented DBMS
Time Series DBMSRelational DBMS
Secondary database modelsDocument store
Spatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score4.36
Rank#72  Overall
#12  Document stores
Score8.08
Rank#48  Overall
#31  Relational DBMS
Score0.06
Rank#380  Overall
#50  Document stores
#18  Object oriented DBMS
Score0.06
Rank#383  Overall
#43  Time Series DBMS
Websitecloud.google.com/­datastoregreenplum.orgorigodb.comgithub.com/­sitewhere/­sitewhere
Technical documentationcloud.google.com/­datastore/­docsdocs.greenplum.orgorigodb.com/­docssitewhere1.sitewhere.io/­index.html
DeveloperGooglePivotal Software Inc.Robert Friberg et alSiteWhereTeradata
Initial release200820052009 infounder the name LiveDB20102005
Current release7.0.0, September 2023
License infoCommercial or Open SourcecommercialOpen Source infoApache 2.0Open SourceOpen Source infoCommon Public Attribution License Version 1.0commercial
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 languageC#Java
Server operating systemshostedLinuxLinux
Windows
Linux
OS X
Windows
Linux
Data schemeschema-freeyesyespredefined schemeFlexible Schema (defined schema, partial schema, schema free) infodefined schema within the relational store; partial schema or schema free in the Aster File Store
Typing infopredefined data types such as float or dateyes, details hereyesUser defined using .NET types and collectionsyesyes
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 4.2no infocan be achieved using .NETnoyes infoin Aster File Store
Secondary indexesyesyesyesnoyes
SQL infoSupport of SQLSQL-like query language (GQL)yesnonoyes
APIs and other access methodsgRPC (using protocol buffers) API
RESTful HTTP/JSON API
JDBC
ODBC
.NET Client API
HTTP API
LINQ
HTTP RESTADO.NET
JDBC
ODBC
OLE DB
Supported programming languages.Net
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
C
Java
Perl
Python
R
.NetC
C#
C++
Java
Python
R
Server-side scripts infoStored proceduresusing Google App EngineyesyesR packages
TriggersCallbacks using the Google Apps Engineyesyes infoDomain Eventsno
Partitioning methods infoMethods for storing different data on different nodesShardingShardinghorizontal partitioning infoclient side managed; servers are not synchronizedSharding infobased on HBaseSharding
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication using PaxosSource-replica replicationSource-replica replicationselectable replication factor infobased on HBaseyes infoDimension tables are replicated across all nodes in the cluster. The number of replicas for the file store can be configured.
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes infousing Google Cloud Dataflowyesnonoyes infoSQL Map-Reduce Framework
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 ConsistencyImmediate Consistency or Eventual Consistency depending on configuration
Foreign keys infoReferential integrityyes infovia ReferenceProperties or Ancestor pathsyesdepending on modelnono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACID infoSerializable Isolation within Transactions, Read Committed outside of TransactionsACIDACIDnoACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
Durability infoSupport for making data persistentyesyesyes infoWrite ahead logyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.nonoyesnono
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-standardRole based authorizationUsers with fine-grained authorization conceptfine grained access rights according to SQL-standard

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More resources
Google Cloud DatastoreGreenplumOrigoDBSiteWhereTeradata Aster
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