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DBMS > Google BigQuery vs. MarkLogic vs. Microsoft SQL Server vs. Splice Machine

System Properties Comparison Google BigQuery vs. MarkLogic vs. Microsoft SQL Server vs. Splice Machine

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Editorial information provided by DB-Engines
NameGoogle BigQuery  Xexclude from comparisonMarkLogic  Xexclude from comparisonMicrosoft SQL Server  Xexclude from comparisonSplice Machine  Xexclude from comparison
DescriptionLarge scale data warehouse service with append-only tablesOperational and transactional Enterprise NoSQL databaseMicrosofts flagship relational DBMSOpen-Source SQL RDBMS for Operational and Analytical use cases with native Machine Learning, powered by Hadoop and Spark
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
Score0.54
Rank#252  Overall
#115  Relational DBMS
Websitecloud.google.com/­bigquerywww.progress.com/­marklogicwww.microsoft.com/­en-us/­sql-serversplicemachine.com
Technical documentationcloud.google.com/­bigquery/­docswww.progress.com/­marklogic/­documentationlearn.microsoft.com/­en-US/­sql/­sql-serversplicemachine.com/­how-it-works
DeveloperGoogleMarkLogic Corp.MicrosoftSplice Machine
Initial release2010200119892014
Current release11.0, December 2022SQL Server 2022, November 20223.1, March 2021
License infoCommercial or Open Sourcecommercialcommercial inforestricted free version is availablecommercial inforestricted free version is availableOpen Source infoAGPL 3.0, commercial license available
Cloud-based only infoOnly available as a cloud serviceyesnonono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC++C++Java
Server operating systemshostedLinux
OS X
Windows
Linux
Windows
Linux
OS X
Solaris
Windows
Data schemeyesschema-free infoSchema can be enforcedyesyes
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.noyesyes
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)
JDBC
Native Spark Datasource
ODBC
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++
Java
JavaScript (Node.js)
Python
R
Scala
Server-side scripts infoStored proceduresuser defined functions infoin JavaScriptyes infovia XQuery or JavaScriptTransact SQL, .NET languages, R, Python and (with SQL Server 2019) Javayes infoJava
Triggersnoyesyesyes
Partitioning methods infoMethods for storing different data on different nodesnoneShardingtables can be distributed across several files (horizontal partitioning); sharding through federationShared Nothhing Auto-Sharding, Columnar Partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesyesyes, but depending on the SQL-Server EditionMulti-source replication
Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyes infovia Hadoop Connector, HDFS Direct Access and in-database MapReduce jobsnoYes, via Full Spark Integration
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integritynonoyesyes
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, multi-version concurrency control (MVCC)
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 Indexesyesyes
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-standardAccess rights for users, groups and roles according to SQL-standard

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More resources
Google BigQueryMarkLogicMicrosoft SQL ServerSplice Machine
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