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DBMS > Dolt vs. Faircom EDGE vs. GridGain vs. Splice Machine

System Properties Comparison Dolt vs. Faircom EDGE vs. GridGain vs. Splice Machine

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Editorial information provided by DB-Engines
NameDolt  Xexclude from comparisonFaircom EDGE infoformerly c-treeEDGE  Xexclude from comparisonGridGain  Xexclude from comparisonSplice Machine  Xexclude from comparison
DescriptionA MySQL compatible DBMS with Git-like versioning of data and schemaFairCom EDGE is an Industry 4.0 solution built to integrate, collect, aggregate and synchronize mission-critical data in edge computing environmentsGridGain is an in-memory computing platform, built on Apache IgniteOpen-Source SQL RDBMS for Operational and Analytical use cases with native Machine Learning, powered by Hadoop and Spark
Primary database modelRelational DBMSKey-value store
Relational DBMS
Key-value store
Relational DBMS
Relational DBMS
Secondary database modelsDocument store
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.96
Rank#193  Overall
#90  Relational DBMS
Score0.02
Rank#368  Overall
#54  Key-value stores
#156  Relational DBMS
Score1.47
Rank#154  Overall
#26  Key-value stores
#72  Relational DBMS
Score0.54
Rank#250  Overall
#114  Relational DBMS
Websitegithub.com/­dolthub/­dolt
www.dolthub.com
www.faircom.com/­products/­faircom-edgewww.gridgain.comsplicemachine.com
Technical documentationdocs.dolthub.comdocs.faircom.com/­docs/­en/­UUID-23d4f1fd-d213-f6d5-b92e-9b7475baa14e.htmlwww.gridgain.com/­docs/­index.htmlsplicemachine.com/­how-it-works
DeveloperDoltHub IncFairCom CorporationGridGain Systems, Inc.Splice Machine
Initial release2018197920072014
Current releaseV3, October 2020GridGain 8.5.13.1, March 2021
License infoCommercial or Open SourceOpen Source infoApache Version 2.0commercial infoRestricted, free version availablecommercialOpen Source infoAGPL 3.0, commercial license available
Cloud-based only infoOnly available as a cloud servicenononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageGoANSI C, C++Java, C++, .NetJava
Server operating systemsLinux
macOS
Windows
Android
Linux infoARM, x86
Raspbian
Windows
Linux
OS X
Solaris
Windows
Linux
OS X
Solaris
Windows
Data schemeyesFlexible Schema (defined schema, partial schema, schema free)yesyes
Typing infopredefined data types such as float or dateyesyes, ANSI Standard SQL Typesyesyes
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 indexesyesyesyesyes
SQL infoSupport of SQLyesyes infoANSI SQL queriesANSI-99 for query and DML statements, subset of DDLyes
APIs and other access methodsCLI Client
HTTP REST
ADO.NET
Direct SQL
IoT Microservice layer
JDBC
MQTT (Message Queue Telemetry Transport)
ODBC
RESTful HTTP API
HDFS API
Hibernate
JCache
JDBC
ODBC
Proprietary protocol
RESTful HTTP API
Spring Data
JDBC
Native Spark Datasource
ODBC
Supported programming languagesAda
C
C#
C++
D
Delphi
Eiffel
Erlang
Haskell
Java
JavaScript (Node.js)
Objective-C
OCaml
Perl
PHP
Python
Ruby
Scheme
Tcl
C
C#
C++
Java
JavaScript
PHP
Python
VB.Net
C#
C++
Java
PHP
Python
Ruby
Scala
C#
C++
Java
JavaScript (Node.js)
Python
R
Scala
Server-side scripts infoStored proceduresyes infocurrently in alpha releaseyes info.Net, JavaScript, C/C++yes (compute grid and cache interceptors can be used instead)yes infoJava
Triggersyesyesyes (cache interceptors and events)yes
Partitioning methods infoMethods for storing different data on different nodesnoneFile partitioning infoCustomizable business rules for partitioningShardingShared Nothhing Auto-Sharding, Columnar Partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesA database can be cloned to multiple locations and be used there in isolation. Data/schema changes can be pushed/pulled explicitly between locations.yes infoSynchronous and asynchronous realtime replication based on transaction logsyes (replicated cache)Multi-source replication
Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonoyes (compute grid and hadoop accelerator)Yes, via Full Spark Integration
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate Consistency
Tunable Consistency
Immediate ConsistencyImmediate Consistency
Foreign keys infoReferential integrityyesyes infowhen using SQLnoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACIDACIDACID
Concurrency infoSupport for concurrent manipulation of datayesyes infoacross SQL and NoSQLyesyes, 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.yesyesyes
User concepts infoAccess controlOnly one user is configurable, and must be specified in the config file at startupFine grained user, group and file access rights managed across SQL (per ANSI standard) and NoSQL.Security Hooks for custom implementationsAccess rights for users, groups and roles according to SQL-standard

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DoltFaircom EDGE infoformerly c-treeEDGEGridGainSplice Machine
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