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DBMS > DolphinDB vs. Microsoft SQL Server vs. Spark SQL

System Properties Comparison DolphinDB vs. Microsoft SQL Server vs. Spark SQL

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Editorial information provided by DB-Engines
NameDolphinDB  Xexclude from comparisonMicrosoft SQL Server  Xexclude from comparisonSpark SQL  Xexclude from comparison
DescriptionDolphinDB is a high performance Time Series DBMS. It is integrated with an easy-to-use fully featured programming language and a high-volume high-velocity streaming analytics system. It offers operational simplicity, scalability, fault tolerance, and concurrency.Microsofts flagship relational DBMSSpark SQL is a component on top of 'Spark Core' for structured data processing
Primary database modelTime Series DBMSRelational DBMSRelational DBMS
Secondary database modelsRelational DBMSDocument store
Graph DBMS
Spatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score2.85
Rank#114  Overall
#7  Time Series DBMS
Score929.09
Rank#3  Overall
#3  Relational DBMS
Score19.74
Rank#36  Overall
#22  Relational DBMS
Websitewww.dolphindb.comwww.microsoft.com/­en-us/­sql-serverspark.apache.org/­sql
Technical documentationwww.dolphindb.com/­helpdocs.microsoft.com/­en-US/­sql/­sql-serverspark.apache.org/­docs/­latest/­sql-programming-guide.html
DeveloperDolphinDB, IncMicrosoftApache Software Foundation
Initial release201819892014
Current releasev2.00.4, January 2022SQL Server 2022, November 20223.3.0 ( 2.13), June 2022
License infoCommercial or Open Sourcecommercial infofree community version availablecommercial inforestricted free version is availableOpen Source infoApache 2.0
Cloud-based only infoOnly available as a cloud servicenonono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC++C++Scala
Server operating systemsLinux
Windows
Linux
Windows
Linux
OS X
Windows
Data schemeyesyesyes
Typing infopredefined data types such as float or dateyesyesyes
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.noyesno
Secondary indexesyesyesno
SQL infoSupport of SQLSQL-like query languageyesSQL-like DML and DDL statements
APIs and other access methodsJDBC
JSON over HTTP
Kafka
MQTT (Message Queue Telemetry Transport)
ODBC
OPC DA
OPC UA
RabbitMQ
WebSocket
ADO.NET
JDBC
ODBC
OLE DB
Tabular Data Stream (TDS)
JDBC
ODBC
Supported programming languagesC#
C++
Go
Java
JavaScript
MatLab
Python
R
Rust
C#
C++
Delphi
Go
Java
JavaScript (Node.js)
PHP
Python
R
Ruby
Visual Basic
Java
Python
R
Scala
Server-side scripts infoStored proceduresyesTransact SQL, .NET languages, R, Python and (with SQL Server 2019) Javano
Triggersnoyesno
Partitioning methods infoMethods for storing different data on different nodeshorizontal partitioningtables can be distributed across several files (horizontal partitioning); sharding through federationyes, utilizing Spark Core
Replication methods infoMethods for redundantly storing data on multiple nodesyesyes, but depending on the SQL-Server Editionnone
MapReduce infoOffers an API for user-defined Map/Reduce methodsyesno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integritynoyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datayesACIDno
Concurrency infoSupport for concurrent manipulation of datayesyesyes
Durability infoSupport for making data persistentyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesyesno
User concepts infoAccess controlAdministrators, Users, Groupsfine grained access rights according to SQL-standardno

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More resources
DolphinDBMicrosoft SQL ServerSpark SQL
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