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DBMS > FatDB vs. Splice Machine vs. Stardog vs. Vitess

System Properties Comparison FatDB vs. Splice Machine vs. Stardog vs. Vitess

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Editorial information provided by DB-Engines
NameFatDB  Xexclude from comparisonSplice Machine  Xexclude from comparisonStardog  Xexclude from comparisonVitess  Xexclude from comparison
FatDB/FatCloud has ceased operations as a company with February 2014. FatDB is discontinued and excluded from the ranking.
DescriptionA .NET NoSQL DBMS that can integrate with and extend SQL Server.Open-Source SQL RDBMS for Operational and Analytical use cases with native Machine Learning, powered by Hadoop and SparkEnterprise Knowledge Graph platform and graph DBMS with high availability, high performance reasoning, and virtualizationScalable, distributed, cloud-native DBMS, extending MySQL
Primary database modelDocument store
Key-value store
Relational DBMSGraph DBMS
RDF store
Relational DBMS
Secondary database modelsDocument store
Spatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.54
Rank#250  Overall
#114  Relational DBMS
Score2.02
Rank#123  Overall
#11  Graph DBMS
#6  RDF stores
Score0.82
Rank#209  Overall
#97  Relational DBMS
Websitesplicemachine.comwww.stardog.comvitess.io
Technical documentationsplicemachine.com/­how-it-worksdocs.stardog.comvitess.io/­docs
DeveloperFatCloudSplice MachineStardog-UnionThe Linux Foundation, PlanetScale
Initial release2012201420102013
Current release3.1, March 20217.3.0, May 202015.0.2, December 2022
License infoCommercial or Open SourcecommercialOpen Source infoAGPL 3.0, commercial license availablecommercial info60-day fully-featured trial license; 1-year fully-featured non-commercial use license for academics/studentsOpen Source infoApache Version 2.0, commercial licenses 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#JavaJavaGo
Server operating systemsWindowsLinux
OS X
Solaris
Windows
Linux
macOS
Windows
Docker
Linux
macOS
Data schemeschema-freeyesschema-free and OWL/RDFS-schema supportyes
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.no infoImport/export of XML data possible
Secondary indexesyesyesyes infosupports real-time indexing in full-text and geospatialyes
SQL infoSupport of SQLno infoVia inetgration in SQL ServeryesYes, compatible with all major SQL variants through dedicated BI/SQL Serveryes infowith proprietary extensions
APIs and other access methods.NET Client API
LINQ
RESTful HTTP API
RPC
Windows WCF Bindings
JDBC
Native Spark Datasource
ODBC
GraphQL query language
HTTP API
Jena RDF API
OWL
RDF4J API
Sesame REST HTTP Protocol
SNARL
SPARQL
Spring Data
Stardog Studio
TinkerPop 3
ADO.NET
JDBC
MySQL protocol
ODBC
Supported programming languagesC#C#
C++
Java
JavaScript (Node.js)
Python
R
Scala
.Net
Clojure
Groovy
Java
JavaScript
Python
Ruby
Ada
C
C#
C++
D
Delphi
Eiffel
Erlang
Haskell
Java
JavaScript (Node.js)
Objective-C
OCaml
Perl
PHP
Python
Ruby
Scheme
Tcl
Server-side scripts infoStored proceduresyes infovia applicationsyes infoJavauser defined functions and aggregates, HTTP Server extensions in Javayes infoproprietary syntax
Triggersyes infovia applicationsyesyes infovia event handlersyes
Partitioning methods infoMethods for storing different data on different nodesShardingShared Nothhing Auto-Sharding, Columnar PartitioningnoneSharding
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication factorMulti-source replication
Source-replica replication
Multi-source replication in HA-ClusterMulti-source replication
Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsyesYes, via Full Spark Integrationnono
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual Consistency
Immediate Consistency
Immediate ConsistencyImmediate Consistency in HA-ClusterEventual Consistency across shards
Immediate Consistency within a shard
Foreign keys infoReferential integritynoyesyes inforelationships in graphsyes infonot for MyISAM storage engine
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACIDACIDACID at shard level
Concurrency infoSupport for concurrent manipulation of datayesyes, multi-version concurrency control (MVCC)yesyes infotable locks or row locks depending on storage engine
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 controlno infoCan implement custom security layer via applicationsAccess rights for users, groups and roles according to SQL-standardAccess rights for users and rolesUsers with fine-grained authorization concept infono user groups or roles

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More resources
FatDBSplice MachineStardogVitess
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