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DBMS > Google Cloud Datastore vs. Ingres vs. ObjectBox vs. SQream DB vs. Teradata

System Properties Comparison Google Cloud Datastore vs. Ingres vs. ObjectBox vs. SQream DB vs. Teradata

Editorial information provided by DB-Engines
NameGoogle Cloud Datastore  Xexclude from comparisonIngres  Xexclude from comparisonObjectBox  Xexclude from comparisonSQream DB  Xexclude from comparisonTeradata  Xexclude from comparison
DescriptionAutomatically scaling NoSQL Database as a Service (DBaaS) on the Google Cloud PlatformWell established RDBMSExtremely fast embedded database for small devices, IoT and Mobilea GPU-based, columnar RDBMS for big data analytics workloadsA hybrid cloud data analytics software platform (Teradata Vantage)
Primary database modelDocument storeRelational DBMSObject oriented DBMSRelational DBMSRelational DBMS
Secondary database modelsTime Series DBMSDocument store
Graph 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
Score4.11
Rank#81  Overall
#44  Relational DBMS
Score1.20
Rank#170  Overall
#5  Object oriented DBMS
Score0.70
Rank#227  Overall
#104  Relational DBMS
Score45.33
Rank#21  Overall
#15  Relational DBMS
Websitecloud.google.com/­datastorewww.actian.com/­databases/­ingresobjectbox.iosqream.comwww.teradata.com
Technical documentationcloud.google.com/­datastore/­docsdocs.actian.com/­ingresdocs.objectbox.iodocs.sqream.comdocs.teradata.com
DeveloperGoogleActian CorporationObjectBox LimitedSQream TechnologiesTeradata
Initial release20081974 infooriginally developed at University Berkely in early 1970s201720171984
Current release11.2, May 20222022.1.6, December 2022Teradata Vantage 1.0 MU2, January 2019
License infoCommercial or Open SourcecommercialcommercialOpen Source infoApache License 2.0commercialcommercial
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 languageCC and C++C++, CUDA, Haskell, Java, Scala
Server operating systemshostedAIX
HP Open VMS
HP-UX
Linux
Solaris
Windows
Android
iOS
Linux
macOS
Windows
Linuxhosted
Linux
Data schemeschema-freeyesyesyesyes
Typing infopredefined data types such as float or dateyes, details hereyesyesyes, ANSI Standard SQL Typesyes
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.nono infobut tools for importing/exporting data from/to XML-files availablenoyes
Secondary indexesyesyesyesnoyes infoJoin-index to prejoin tables, aggregate index, sparse index, hash index
SQL infoSupport of SQLSQL-like query language (GQL)yesnoyesyes infoSQL 2016 + extensions
APIs and other access methodsgRPC (using protocol buffers) API
RESTful HTTP/JSON API
.NET Client API
JDBC
ODBC
proprietary protocol (OpenAPI)
Proprietary native API.Net
JDBC
ODBC
.NET Client API
HTTP REST
JDBC
JMS Adapter
ODBC
OLE DB
Supported programming languages.Net
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
C
C++
Dart
Go
Java
JavaScript infoplanned (as of Jan 2019)
Kotlin
Python infoplanned (as of Jan 2019)
Swift
C++
Java
JavaScript (Node.js)
Python
C
C++
Cobol
Java (JDBC-ODBC)
Perl
PL/1
Python
R
Ruby
Server-side scripts infoStored proceduresusing Google App Engineyesnouser defined functions in Pythonyes infoUDFs, stored procedures, table functions in parallel
TriggersCallbacks using the Google Apps Engineyesnonoyes
Partitioning methods infoMethods for storing different data on different nodesShardinghorizontal partitioning infoIngres Star to access multiple databases simultaneouslynonehorizontal and vertical partitioningSharding infoHashing
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication using PaxosIngres Replicatoronline/offline synchronization between client and servernoneMulti-source replication
Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes infousing Google Cloud Dataflownononono
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 ConsistencyImmediate Consistency
Foreign keys infoReferential integrityyes infovia ReferenceProperties or Ancestor pathsyesyesnoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACID infoSerializable Isolation within Transactions, Read Committed outside of TransactionsACIDACIDACIDACID
Concurrency infoSupport for concurrent manipulation of datayesyes infoMVCCyesyesyes
Durability infoSupport for making data persistentyesyesyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.nononoyes
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-standardyesfine grained access rights according to SQL-standard
More information provided by the system vendor
Google Cloud DatastoreIngresObjectBoxSQream DBTeradata
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More resources
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