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DBMS > EXASOL vs. FatDB vs. Splice Machine

System Properties Comparison EXASOL vs. FatDB vs. Splice Machine

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Editorial information provided by DB-Engines
NameEXASOL  Xexclude from comparisonFatDB  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.
DescriptionHigh-performance, in-memory, MPP database specifically designed for in-memory analytics.A .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 Spark
Primary database modelRelational DBMSDocument store
Key-value store
Relational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score2.47
Rank#119  Overall
#57  Relational DBMS
Score0.54
Rank#257  Overall
#118  Relational DBMS
Websitewww.exasol.comsplicemachine.com
Technical documentationwww.exasol.com/­resourcessplicemachine.com/­how-it-works
DeveloperExasolFatCloudSplice Machine
Initial release200020122014
Current release3.1, March 2021
License infoCommercial or Open SourcecommercialcommercialOpen Source infoAGPL 3.0, commercial license available
Cloud-based only infoOnly available as a cloud servicenonono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageC#Java
Server operating systemsWindowsLinux
OS X
Solaris
Windows
Data schemeyesschema-freeyes
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.no
Secondary indexesyesyesyes
SQL infoSupport of SQLyesno infoVia inetgration in SQL Serveryes
APIs and other access methods.Net
JDBC
ODBC
WebSocket
.NET Client API
LINQ
RESTful HTTP API
RPC
Windows WCF Bindings
JDBC
Native Spark Datasource
ODBC
Supported programming languagesJava
Lua
Python
R
C#C#
C++
Java
JavaScript (Node.js)
Python
R
Scala
Server-side scripts infoStored proceduresuser defined functionsyes infovia applicationsyes infoJava
Triggersyesyes infovia applicationsyes
Partitioning methods infoMethods for storing different data on different nodesShardingShardingShared Nothhing Auto-Sharding, Columnar Partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication factorMulti-source replication
Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes infoHadoop integrationyesYes, via Full Spark Integration
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyEventual Consistency
Immediate Consistency
Immediate Consistency
Foreign keys infoReferential integrityyesnoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDnoACID
Concurrency infoSupport for concurrent manipulation of datayesyesyes, multi-version concurrency control (MVCC)
Durability infoSupport for making data persistentyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesyes
User concepts infoAccess controlAccess rights for users, groups and roles according to SQL-standardno infoCan implement custom security layer via applicationsAccess rights for users, groups and roles according to SQL-standard

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More resources
EXASOLFatDBSplice Machine
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