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DBMS > FatDB vs. Ingres vs. Microsoft Azure Synapse Analytics vs. RDF4J vs. Splice Machine

System Properties Comparison FatDB vs. Ingres vs. Microsoft Azure Synapse Analytics vs. RDF4J vs. Splice Machine

Editorial information provided by DB-Engines
NameFatDB  Xexclude from comparisonIngres  Xexclude from comparisonMicrosoft Azure Synapse Analytics infopreviously named Azure SQL Data Warehouse  Xexclude from comparisonRDF4J infoformerly known as Sesame  Xexclude from comparisonSplice Machine  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.Well established RDBMSElastic, large scale data warehouse service leveraging the broad eco-system of SQL ServerRDF4J is a Java framework for processing RDF data, supporting both memory-based and a disk-based storage.Open-Source SQL RDBMS for Operational and Analytical use cases with native Machine Learning, powered by Hadoop and Spark
Primary database modelDocument store
Key-value store
Relational DBMSRelational DBMSRDF storeRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score3.80
Rank#82  Overall
#44  Relational DBMS
Score19.93
Rank#31  Overall
#19  Relational DBMS
Score0.74
Rank#222  Overall
#9  RDF stores
Score0.54
Rank#252  Overall
#115  Relational DBMS
Websitewww.actian.com/­databases/­ingresazure.microsoft.com/­services/­synapse-analyticsrdf4j.orgsplicemachine.com
Technical documentationdocs.actian.com/­ingresdocs.microsoft.com/­azure/­synapse-analyticsrdf4j.org/­documentationsplicemachine.com/­how-it-works
DeveloperFatCloudActian CorporationMicrosoftSince 2016 officially forked into an Eclipse project, former developer was Aduna Software.Splice Machine
Initial release20121974 infooriginally developed at University Berkely in early 1970s201620042014
Current release11.2, May 20223.1, March 2021
License infoCommercial or Open SourcecommercialcommercialcommercialOpen Source infoEclipse Distribution License (EDL), v1.0.Open Source infoAGPL 3.0, commercial license available
Cloud-based only infoOnly available as a cloud servicenonoyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageC#CC++JavaJava
Server operating systemsWindowsAIX
HP Open VMS
HP-UX
Linux
Solaris
Windows
hostedLinux
OS X
Unix
Windows
Linux
OS X
Solaris
Windows
Data schemeschema-freeyesyesyes infoRDF Schemasyes
Typing infopredefined data types such as float or dateyesyesyesyesyes
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 infobut tools for importing/exporting data from/to XML-files availableno
Secondary indexesyesyesyesyesyes
SQL infoSupport of SQLno infoVia inetgration in SQL Serveryesyesnoyes
APIs and other access methods.NET Client API
LINQ
RESTful HTTP API
RPC
Windows WCF Bindings
.NET Client API
JDBC
ODBC
proprietary protocol (OpenAPI)
ADO.NET
JDBC
ODBC
Java API
RIO infoRDF Input/Output
Sail API
SeRQL infoSesame RDF Query Language
Sesame REST HTTP Protocol
SPARQL
JDBC
Native Spark Datasource
ODBC
Supported programming languagesC#C#
Java
PHP
Java
PHP
Python
C#
C++
Java
JavaScript (Node.js)
Python
R
Scala
Server-side scripts infoStored proceduresyes infovia applicationsyesTransact SQLyesyes infoJava
Triggersyes infovia applicationsyesnoyesyes
Partitioning methods infoMethods for storing different data on different nodesShardinghorizontal partitioning infoIngres Star to access multiple databases simultaneouslySharding, horizontal partitioningnoneShared Nothhing Auto-Sharding, Columnar Partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication factorIngres ReplicatoryesnoneMulti-source replication
Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsyesnononoYes, via Full Spark Integration
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual Consistency
Immediate Consistency
Immediate ConsistencyImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integritynoyesno infodocs.microsoft.com/­en-us/­azure/­synapse-analytics/­sql-data-warehouse/­sql-data-warehouse-table-constraintsyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACIDACIDACID infoIsolation support depends on the API usedACID
Concurrency infoSupport for concurrent manipulation of datayesyes infoMVCCyesyesyes, multi-version concurrency control (MVCC)
Durability infoSupport for making data persistentyesyesyesyes infoin-memory storage is supported as wellyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyes
User concepts infoAccess controlno infoCan implement custom security layer via applicationsfine grained access rights according to SQL-standardyesnoAccess rights for users, groups and roles according to SQL-standard

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More resources
FatDBIngresMicrosoft Azure Synapse Analytics infopreviously named Azure SQL Data WarehouseRDF4J infoformerly known as SesameSplice Machine
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