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DBMS > atoti vs. Fujitsu Enterprise Postgres vs. Splice Machine

System Properties Comparison atoti vs. Fujitsu Enterprise Postgres vs. Splice Machine

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Editorial information provided by DB-Engines
Nameatoti  Xexclude from comparisonFujitsu Enterprise Postgres  Xexclude from comparisonSplice Machine  Xexclude from comparison
DescriptionAn in-memory DBMS combining transactional and analytical processing to handle the aggregation of ever-changing data.Enterprise-grade PostgreSQL-based DBMS with security enhancements such as Transparent Data Encryption and Data Masking, plus high-availability and performance improvement features.Open-Source SQL RDBMS for Operational and Analytical use cases with native Machine Learning, powered by Hadoop and Spark
Primary database modelObject oriented DBMSRelational DBMSRelational DBMS
Secondary database modelsDocument store
Spatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.61
Rank#243  Overall
#10  Object oriented DBMS
Score0.37
Rank#278  Overall
#128  Relational DBMS
Score0.54
Rank#252  Overall
#115  Relational DBMS
Websiteatoti.iowww.postgresql.fastware.comsplicemachine.com
Technical documentationdocs.atoti.iowww.postgresql.fastware.com/­product-manualssplicemachine.com/­how-it-works
DeveloperActiveViamPostgreSQL Global Development Group, Fujitsu Australia Software TechnologySplice Machine
Initial release2014
Current releaseFujitsu Enterprise Postgres 14, January 20223.1, March 2021
License infoCommercial or Open Sourcecommercial infofree versions availablecommercialOpen Source infoAGPL 3.0, commercial license available
Cloud-based only infoOnly available as a cloud servicenonono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaCJava
Server operating systemsLinux
Windows
Linux
OS X
Solaris
Windows
Data schemeyesyes
Typing infopredefined data types such as float or dateyesyes
Secondary indexesyesyes
SQL infoSupport of SQLMultidimensional Expressions (MDX)yesyes
APIs and other access methodsADO.NET
JDBC
native C library
ODBC
streaming API for large objects
JDBC
Native Spark Datasource
ODBC
Supported programming languages.Net
C
C++
Delphi
Java
JavaScript (Node.js)
Perl
PHP
Python
Tcl
C#
C++
Java
JavaScript (Node.js)
Python
R
Scala
Server-side scripts infoStored proceduresPythonuser defined functionsyes infoJava
Triggersyesyes
Partitioning methods infoMethods for storing different data on different nodesSharding, horizontal partitioningpartitioning by range, list and by hashShared Nothhing Auto-Sharding, Columnar Partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesSource-replica replicationMulti-source replication
Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonoYes, via Full Spark Integration
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integrityyesyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACID
Concurrency infoSupport for concurrent manipulation of datayes, multi-version concurrency control (MVCC)yes, multi-version concurrency control (MVCC)yes, multi-version concurrency control (MVCC)
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.yesyes
User concepts infoAccess controlfine grained access rights according to SQL-standardAccess rights for users, groups and roles according to SQL-standard

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atotiFujitsu Enterprise PostgresSplice Machine
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