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DBMS > 4D vs. GridDB vs. Postgres-XL vs. SingleStore

System Properties Comparison 4D vs. GridDB vs. Postgres-XL vs. SingleStore

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Editorial information provided by DB-Engines
Name4D infoformer name: 4th Dimension  Xexclude from comparisonGridDB  Xexclude from comparisonPostgres-XL  Xexclude from comparisonSingleStore infoformer name was MemSQL  Xexclude from comparison
DescriptionApplication development environment with integrated database management systemScalable in-memory time series database optimized for IoT and Big DataBased on PostgreSQL enhanced with MPP and write-scale-out cluster featuresMySQL 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 DBMSTime Series DBMSRelational DBMSRelational DBMS
Secondary database modelsKey-value store
Relational DBMS
Document store
Spatial DBMS
Document store
Spatial DBMS
Time Series DBMS
Vector DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score2.37
Rank#110  Overall
#54  Relational DBMS
Score1.91
Rank#123  Overall
#10  Time Series DBMS
Score0.43
Rank#260  Overall
#119  Relational DBMS
Score4.02
Rank#74  Overall
#39  Relational DBMS
Websitewww.4d.comgriddb.netwww.postgres-xl.orgwww.singlestore.com
Technical documentationdeveloper.4d.comdocs.griddb.netwww.postgres-xl.org/­documentationdocs.singlestore.com
Developer4D, IncToshiba CorporationSingleStore Inc.
Initial release198420132014 infosince 2012, originally named StormDB2013
Current releasev20, April 20235.1, August 202210 R1, October 20188.5, January 2024
License infoCommercial or Open SourcecommercialOpen Source infoAGPL version 3 and Apache License, version 2.0 , commercial license (standard and advanced editions) also availableOpen Source infoMozilla public licensecommercial infofree developer edition available
Cloud-based only infoOnly available as a cloud servicenononono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageC++CC++, Go
Server operating systemsOS X
Windows
LinuxLinux
macOS
Linux info64 bit version required
Data schemeyesyesyesyes
Typing infopredefined data types such as float or dateyesyes infonumerical, string, blob, geometry, boolean, timestampyesyes
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.yesnoyes infoXML type, but no XML query functionalityno
Secondary indexesyesyesyesyes
SQL infoSupport of SQLyes infoclose to SQL 92SQL92, SQL-like TQL (Toshiba Query Language)yes infodistributed, parallel query executionyes infobut no triggers and foreign keys
APIs and other access methodsODBC
RESTful HTTP API infoby using 4D Mobile
SOAP webservices
JDBC
ODBC
Proprietary protocol
RESTful HTTP/JSON API
ADO.NET
JDBC
native C library
ODBC
streaming API for large objects
Cluster Management API infoas HTTP Rest and CLI
HTTP API
JDBC
MongoDB API
ODBC
Supported programming languages4D proprietary IDE
PHP
C
C++
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
Ruby
.Net
C
C++
Delphi
Erlang
Java
JavaScript (Node.js)
Perl
PHP
Python
Tcl
Bash
C
C#
Java
JavaScript (Node.js)
Python
Server-side scripts infoStored proceduresyesnouser defined functionsyes
Triggersyesyesyesno
Partitioning methods infoMethods for storing different data on different nodesnoneShardinghorizontal partitioningSharding infohash partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replicationSource-replica replicationSource-replica replication infostores two copies of each physical data partition on two separate nodes
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoConnector for using GridDB as an input source and output destination for Hadoop MapReduce jobsnono infocan define user-defined aggregate functions for map-reduce-style calculations
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate consistency within container, eventual consistency across containersImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integrityyesnoyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACID at container levelACID infoMVCCACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes, multi-version concurrency control (MVCC)
Durability infoSupport for making data persistentyesyesyesyes 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.noyesnoyes
User concepts infoAccess controlUsers and groupsAccess rights for users can be defined per databasefine grained access rights according to SQL-standardFine grained access control via users, groups and roles

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More resources
4D infoformer name: 4th DimensionGridDBPostgres-XLSingleStore infoformer name was MemSQL
DB-Engines blog posts

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Recent citations in the news

TOSHIBA DIGITAL SOLUTIONS CORPORATION
1 November 2020, global.toshiba

Toshiba launches cloudy managed IoT database service running its own GridDB
8 April 2021, The Register

Now Features Scale-Out and Scale-Up combo for Petabyte-scale Data Management
3 December 2019, global.toshiba

’s SQL Interface, Aims to Accelerate Open Innovation
17 June 2020, global.toshiba

IoT: Opt for the Right Open Source Database
11 August 2023, Open Source For You

provided by Google News

SingleStore Partners With Snowflake to Help Users Build Faster, More Efficient Real Time AI Applications
19 September 2024, businesswire.com

SingleStore CEO sees little future for purpose-built vector databases
24 January 2024, VentureBeat

Achieve near real-time analytics on Amazon DynamoDB with SingleStore
16 September 2024, AWS Blog

Building a Modern Database: Nikita Shamgunov on Postgres and Beyond
18 April 2024, Madrona Venture Group

SingleStore: We do vectors and you don’t need knowledge graphs
22 July 2024, Blocks & Files

provided by Google News



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