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DBMS > Apache Spark (SQL) vs. Dolt vs. SingleStore

System Properties Comparison Apache Spark (SQL) vs. Dolt vs. SingleStore

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Editorial information provided by DB-Engines
NameApache Spark (SQL)  Xexclude from comparisonDolt  Xexclude from comparisonSingleStore infoformer name was MemSQL  Xexclude from comparison
DescriptionApache Spark SQL is a component on top of 'Spark Core' for structured data processingA MySQL compatible DBMS with Git-like versioning of data and schemaMySQL wire-compliant distributed RDBMS that combines an in-memory row-oriented and a disc-based column-oriented storage with patented universal storage to handle transactional and analytical workloads in one single table type
Primary database modelRelational DBMSRelational DBMSRelational DBMS
Secondary database modelsDocument storeDocument store
Spatial DBMS
Time Series DBMS
Vector DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score17.39
Rank#32  Overall
#20  Relational DBMS
Score0.77
Rank#213  Overall
#100  Relational DBMS
Score4.13
Rank#69  Overall
#37  Relational DBMS
Websitespark.apache.org/­sqlgithub.com/­dolthub/­dolt
www.dolthub.com
www.singlestore.com
Technical documentationspark.apache.org/­docs/­latest/­sql-programming-guide.htmldocs.dolthub.comdocs.singlestore.com
DeveloperApache Software FoundationDoltHub IncSingleStore Inc.
Initial release201420182013
Current release3.5.0 ( 2.13), September 20238.5, January 2024
License infoCommercial or Open SourceOpen Source infoApache 2.0Open Source infoApache Version 2.0commercial infofree developer edition available
Cloud-based only infoOnly available as a cloud servicenonono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageScalaGoC++, Go
Server operating systemsLinux
OS X
Windows
Linux
macOS
Windows
Linux info64 bit version required
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.nonono
Secondary indexesnoyesyes
SQL infoSupport of SQLSQL-like DML and DDL statementsyesyes infobut no triggers and foreign keys
APIs and other access methodsJDBC
ODBC
CLI Client
HTTP REST
Cluster Management API infoas HTTP Rest and CLI
HTTP API
JDBC
MongoDB API
ODBC
Supported programming languagesJava
Python
R
Scala
Ada
C
C#
C++
D
Delphi
Eiffel
Erlang
Haskell
Java
JavaScript (Node.js)
Objective-C
OCaml
Perl
PHP
Python
Ruby
Scheme
Tcl
Bash
C
C#
Java
JavaScript (Node.js)
Python
Server-side scripts infoStored proceduresnoyes infocurrently in alpha releaseyes
Triggersnoyesno
Partitioning methods infoMethods for storing different data on different nodesyes, utilizing Spark CorenoneSharding infohash partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesnoneA database can be cloned to multiple locations and be used there in isolation. Data/schema changes can be pushed/pulled explicitly between locations.Source-replica replication infostores two copies of each physical data partition on two separate nodes
MapReduce infoOffers an API for user-defined Map/Reduce methodsnono infocan define user-defined aggregate functions for map-reduce-style calculations
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate Consistency
Foreign keys infoReferential integritynoyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACIDACID
Concurrency infoSupport for concurrent manipulation of datayesyesyes, multi-version concurrency control (MVCC)
Durability infoSupport for making data persistentyesyesyes infoAll updates are persistent, including those to disk-based columnstores and memory-based row stores. Transaction commits are supported via write-ahead log.
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyes
User concepts infoAccess controlnoOnly one user is configurable, and must be specified in the config file at startupFine grained access control via users, groups and roles

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More resources
Apache Spark (SQL)DoltSingleStore infoformer name was MemSQL
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SingleStore: The Increasing Momentum of Multi-Model Database Systems
14 February 2022,  Akmal Chaudhri, SingleStore (sponsor) 

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