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DBMS > atoti vs. FatDB vs. Spark SQL vs. Ultipa

System Properties Comparison atoti vs. FatDB vs. Spark SQL vs. Ultipa

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Editorial information provided by DB-Engines
Nameatoti  Xexclude from comparisonFatDB  Xexclude from comparisonSpark SQL  Xexclude from comparisonUltipa  Xexclude from comparison
FatDB/FatCloud has ceased operations as a company with February 2014. FatDB is discontinued and excluded from the ranking.
DescriptionAn in-memory DBMS combining transactional and analytical processing to handle the aggregation of ever-changing data.A .NET NoSQL DBMS that can integrate with and extend SQL Server.Spark SQL is a component on top of 'Spark Core' for structured data processingHigh performance Graph DBMS supporting HTAP high availability cluster deployment
Primary database modelObject oriented DBMSDocument store
Key-value store
Relational DBMSGraph DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.61
Rank#243  Overall
#11  Object oriented DBMS
Score18.04
Rank#33  Overall
#20  Relational DBMS
Score0.19
Rank#330  Overall
#30  Graph DBMS
Websiteatoti.iospark.apache.org/­sqlwww.ultipa.com
Technical documentationdocs.atoti.iospark.apache.org/­docs/­latest/­sql-programming-guide.htmlwww.ultipa.com/­document
DeveloperActiveViamFatCloudApache Software FoundationUltipa
Initial release201220142019
Current release3.5.0 ( 2.13), September 2023
License infoCommercial or Open Sourcecommercial infofree versions availablecommercialOpen Source infoApache 2.0commercial
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 languageJavaC#Scala
Server operating systemsWindowsLinux
OS X
Windows
Data schemeschema-freeyes
Typing infopredefined data types such as float or dateyesyes
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 indexesyesno
SQL infoSupport of SQLMultidimensional Expressions (MDX)no infoVia inetgration in SQL ServerSQL-like DML and DDL statements
APIs and other access methods.NET Client API
LINQ
RESTful HTTP API
RPC
Windows WCF Bindings
JDBC
ODBC
RESTful HTTP API
Supported programming languagesC#Java
Python
R
Scala
C++
Go
Java
JavaScript (Node.js)
Python
Server-side scripts infoStored proceduresPythonyes infovia applicationsno
Triggersyes infovia applicationsno
Partitioning methods infoMethods for storing different data on different nodesSharding, horizontal partitioningShardingyes, utilizing Spark Core
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication factornone
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyes
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual Consistency
Immediate Consistency
Foreign keys infoReferential integritynono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanono
Concurrency infoSupport for concurrent manipulation of datayes, multi-version concurrency control (MVCC)yesyes
Durability infoSupport for making data persistentyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesno
User concepts infoAccess controlno infoCan implement custom security layer via applicationsno

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More resources
atotiFatDBSpark SQLUltipa
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