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DBMS > Google Cloud Bigtable vs. Microsoft Azure SQL Database vs. RDFox vs. Teradata Aster

System Properties Comparison Google Cloud Bigtable vs. Microsoft Azure SQL Database vs. RDFox vs. Teradata Aster

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Editorial information provided by DB-Engines
NameGoogle Cloud Bigtable  Xexclude from comparisonMicrosoft Azure SQL Database infoformerly SQL Azure  Xexclude from comparisonRDFox  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.
DescriptionGoogle's NoSQL Big Data database service. It's the same database that powers many core Google services, including Search, Analytics, Maps, and Gmail.Database as a Service offering with high compatibility to Microsoft SQL ServerHigh performance knowledge graph and semantic reasoning enginePlatform for big data analytics on multistructured data sources and types
Primary database modelKey-value store
Wide column store
Relational DBMSGraph DBMS
RDF store
Relational DBMS
Secondary database modelsDocument store
Graph DBMS
Spatial DBMS
Relational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score3.15
Rank#95  Overall
#14  Key-value stores
#8  Wide column stores
Score76.78
Rank#16  Overall
#11  Relational DBMS
Score0.29
Rank#300  Overall
#24  Graph DBMS
#13  RDF stores
Websitecloud.google.com/­bigtableazure.microsoft.com/­en-us/­products/­azure-sql/­databasewww.oxfordsemantic.tech
Technical documentationcloud.google.com/­bigtable/­docsdocs.microsoft.com/­en-us/­azure/­azure-sqldocs.oxfordsemantic.tech
DeveloperGoogleMicrosoftOxford Semantic TechnologiesTeradata
Initial release2015201020172005
Current releaseV126.0, Septermber 2022
License infoCommercial or Open Sourcecommercialcommercialcommercialcommercial
Cloud-based only infoOnly available as a cloud serviceyesyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageC++C++
Server operating systemshostedhostedLinux
macOS
Windows
Linux
Data schemeschema-freeyesyes infoRDF schemasFlexible 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 datenoyesyesyes
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.noyesyes infoin Aster File Store
Secondary indexesnoyesyes
SQL infoSupport of SQLnoyesnoyes
APIs and other access methodsgRPC (using protocol buffers) API
HappyBase (Python library)
HBase compatible API (Java)
ADO.NET
JDBC
ODBC
RESTful HTTP API
SPARQL 1.1
ADO.NET
JDBC
ODBC
OLE DB
Supported programming languagesC#
C++
Go
Java
JavaScript (Node.js)
Python
.Net
C#
Java
JavaScript (Node.js)
PHP
Python
Ruby
C
Java
C
C#
C++
Java
Python
R
Server-side scripts infoStored proceduresnoTransact SQLR packages
Triggersnoyesno
Partitioning methods infoMethods for storing different data on different nodesShardingSharding
Replication methods infoMethods for redundantly storing data on multiple nodesInternal replication in Colossus, and regional replication between two clusters in different zonesyes, with always 3 replicas availablereplication via a shared file systemyes 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 methodsyesnoyes infoSQL Map-Reduce Framework
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate consistency (for a single cluster), Eventual consistency (for two or more replicated clusters)Immediate ConsistencyImmediate Consistency in stand-alone mode, Eventual Consistency in replicated setupsImmediate Consistency or Eventual Consistency depending on configuration
Foreign keys infoReferential integritynoyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataAtomic single-row operationsACIDACIDACID
Concurrency infoSupport for concurrent manipulation of datayesyesyes
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)fine grained access rights according to SQL-standardRoles, resources, and access typesfine grained access rights according to SQL-standard

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More resources
Google Cloud BigtableMicrosoft Azure SQL Database infoformerly SQL AzureRDFoxTeradata Aster
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