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DBMS > Google BigQuery vs. MarkLogic vs. Microsoft SQL Server vs. Teradata Aster

System Properties Comparison Google BigQuery vs. MarkLogic vs. Microsoft SQL Server vs. Teradata Aster

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Editorial information provided by DB-Engines
NameGoogle BigQuery  Xexclude from comparisonMarkLogic  Xexclude from comparisonMicrosoft SQL Server  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.
DescriptionLarge scale data warehouse service with append-only tablesOperational and transactional Enterprise NoSQL databaseMicrosofts flagship relational DBMSPlatform for big data analytics on multistructured data sources and types
Primary database modelRelational DBMSDocument store
Native XML DBMS
RDF store infoas of version 7
Search engine
Relational DBMSRelational DBMS
Secondary database modelsDocument store
Graph DBMS
Spatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score58.10
Rank#19  Overall
#13  Relational DBMS
Score5.18
Rank#63  Overall
#11  Document stores
#1  Native XML DBMS
#1  RDF stores
#7  Search engines
Score821.56
Rank#3  Overall
#3  Relational DBMS
Websitecloud.google.com/­bigquerywww.marklogic.comwww.microsoft.com/­en-us/­sql-server
Technical documentationcloud.google.com/­bigquery/­docsdocs.marklogic.comlearn.microsoft.com/­en-US/­sql/­sql-server
DeveloperGoogleMarkLogic Corp.MicrosoftTeradata
Initial release2010200119892005
Current release11.0, December 2022SQL Server 2022, November 2022
License infoCommercial or Open Sourcecommercialcommercial inforestricted free version is availablecommercial inforestricted free version is availablecommercial
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.
SQLServer Flex @ STACKIT offers a managed version of SQL Server with adjustable CPU, RAM, storage amount and speed, in enterprise grade to perfectly match all application requirements. All services are 100% GDPR-compliant.
Implementation languageC++C++
Server operating systemshostedLinux
OS X
Windows
Linux
Windows
Linux
Data schemeyesschema-free infoSchema can be enforcedyesFlexible 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 dateyesyesyesyes
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.noyesyesyes infoin Aster File Store
Secondary indexesnoyesyesyes
SQL infoSupport of SQLyesyes infoSQL92yesyes
APIs and other access methodsRESTful HTTP/JSON APIJava API
Node.js Client API
ODBC
proprietary Optic API infoProprietary Query API, introduced with version 9
RESTful HTTP API
SPARQL
WebDAV
XDBC
XQuery
XSLT
ADO.NET
JDBC
ODBC
OLE DB
Tabular Data Stream (TDS)
ADO.NET
JDBC
ODBC
OLE DB
Supported programming languages.Net
Java
JavaScript
Objective-C
PHP
Python
Ruby
C
C#
C++
Java
JavaScript (Node.js)
Perl
PHP
Python
Ruby
C#
C++
Delphi
Go
Java
JavaScript (Node.js)
PHP
Python
R
Ruby
Visual Basic
C
C#
C++
Java
Python
R
Server-side scripts infoStored proceduresuser defined functions infoin JavaScriptyes infovia XQuery or JavaScriptTransact SQL, .NET languages, R, Python and (with SQL Server 2019) JavaR packages
Triggersnoyesyesno
Partitioning methods infoMethods for storing different data on different nodesnoneShardingtables can be distributed across several files (horizontal partitioning); sharding through federationSharding
Replication methods infoMethods for redundantly storing data on multiple nodesyesyes, but depending on the SQL-Server Editionyes 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 methodsnoyes infovia Hadoop Connector, HDFS Direct Access and in-database MapReduce jobsnoyes infoSQL Map-Reduce Framework
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyImmediate ConsistencyImmediate Consistency or Eventual Consistency depending on configuration
Foreign keys infoReferential integritynonoyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datano infoSince BigQuery is designed for querying dataACID infocan act as a resource manager in an XA/JTA transactionACIDACID
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.noyes, with Range Indexesyesno
User concepts infoAccess controlAccess privileges (owner, writer, reader) on dataset, table or view level infoGoogle Cloud Identity & Access Management (IAM)Role-based access control at the document and subdocument levelsfine grained access rights according to SQL-standardfine grained access rights according to SQL-standard

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More resources
Google BigQueryMarkLogicMicrosoft SQL ServerTeradata Aster
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