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DBMS > FatDB vs. Fujitsu Enterprise Postgres vs. InfluxDB vs. OushuDB vs. Spark SQL

System Properties Comparison FatDB vs. Fujitsu Enterprise Postgres vs. InfluxDB vs. OushuDB vs. Spark SQL

Editorial information provided by DB-Engines
NameFatDB  Xexclude from comparisonFujitsu Enterprise Postgres  Xexclude from comparisonInfluxDB  Xexclude from comparisonOushuDB  Xexclude from comparisonSpark SQL  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.Enterprise-grade PostgreSQL-based DBMS with security enhancements such as Transparent Data Encryption and Data Masking, plus high-availability and performance improvement features.DBMS for storing time series, events and metricsA data warehouse powered by Apache HAWQ supporting descriptive analysis and advanced machine learningSpark SQL is a component on top of 'Spark Core' for structured data processing
Primary database modelDocument store
Key-value store
Relational DBMSTime Series DBMSRelational DBMSRelational DBMS
Secondary database modelsDocument store
Spatial DBMS
Spatial DBMS infowith GEO package
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.31
Rank#285  Overall
#129  Relational DBMS
Score25.83
Rank#28  Overall
#1  Time Series DBMS
Score0.04
Rank#363  Overall
#154  Relational DBMS
Score18.96
Rank#33  Overall
#20  Relational DBMS
Websitewww.postgresql.fastware.comwww.influxdata.com/­products/­influxdb-overviewwww.oushu.com/­product/­oushuDBspark.apache.org/­sql
Technical documentationwww.postgresql.fastware.com/­product-manualsdocs.influxdata.com/­influxdbwww.oushu.com/­documentationspark.apache.org/­docs/­latest/­sql-programming-guide.html
DeveloperFatCloudPostgreSQL Global Development Group, Fujitsu Australia Software TechnologyOushuApache Software Foundation
Initial release201220132014
Current releaseFujitsu Enterprise Postgres 14, January 20222.7.6, April 20244.0.1, August 20203.5.0 ( 2.13), September 2023
License infoCommercial or Open SourcecommercialcommercialOpen Source infoMIT-License; commercial enterprise version availablecommercialOpen Source infoApache 2.0
Cloud-based only infoOnly available as a cloud servicenonononono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageC#CGoScala
Server operating systemsWindowsLinux
Windows
Linux
OS X infothrough Homebrew
LinuxLinux
OS X
Windows
Data schemeschema-freeyesschema-freeyesyes
Typing infopredefined data types such as float or dateyesyesNumeric data and Stringsyesyes
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.nono
Secondary indexesyesyesnoyesno
SQL infoSupport of SQLno infoVia inetgration in SQL ServeryesSQL-like query languageFull-featured ANSI SQL supportSQL-like DML and DDL statements
APIs and other access methods.NET Client API
LINQ
RESTful HTTP API
RPC
Windows WCF Bindings
ADO.NET
JDBC
native C library
ODBC
streaming API for large objects
HTTP API
JSON over UDP
JDBC
ODBC
JDBC
ODBC
Supported programming languagesC#.Net
C
C++
Delphi
Java
JavaScript (Node.js)
Perl
PHP
Python
Tcl
.Net
Clojure
Erlang
Go
Haskell
Java
JavaScript
JavaScript (Node.js)
Lisp
Perl
PHP
Python
R
Ruby
Rust
Scala
C
C++
Java
Python
R
Scala
Server-side scripts infoStored proceduresyes infovia applicationsuser defined functionsnoyesno
Triggersyes infovia applicationsyesnoyesno
Partitioning methods infoMethods for storing different data on different nodesShardingpartitioning by range, list and by hashSharding infoin enterprise version onlyyesyes, utilizing Spark Core
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication factorSource-replica replicationselectable replication factor infoin enterprise version onlynone
MapReduce infoOffers an API for user-defined Map/Reduce methodsyesnonoHadoop integration
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual Consistency
Immediate Consistency
Immediate Consistency
Foreign keys infoReferential integritynoyesnono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACIDnoACIDno
Concurrency infoSupport for concurrent manipulation of datayesyes, multi-version concurrency control (MVCC)yesyesyes
Durability infoSupport for making data persistentyesyesyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yes infoDepending on used storage engineno
User concepts infoAccess controlno infoCan implement custom security layer via applicationsfine grained access rights according to SQL-standardsimple rights management via user accountsKerberos, SSL and role based accessno
More information provided by the system vendor
FatDBFujitsu Enterprise PostgresInfluxDBOushuDBSpark SQL
Specific characteristics100% compatible with community PostgreSQL
» more
InfluxData is the creator of InfluxDB , the open source time series database. It...
» more
Competitive advantagesBuilt-in TDE and Data Masking security. In-Memory Columnar Index, and a high speed...
» more
Time to Value InfluxDB is available in all the popular languages and frameworks,...
» more
Typical application scenariosTransactional payments applications, reporting and mixed workloads.
» more
IoT & Sensor Monitoring Developers are witnessing the instrumentation of every available...
» more
Key customersInfluxData has more than 1,900 paying customers, including customers include MuleSoft,...
» more
Market metricsOver 30 years experience in database technology. Over 20 years in Postgres development...
» more
Fastest-growing database to drive 27,500 GitHub stars Over 750,000 daily active instances
» more
Licensing and pricing modelsCore based licensing
» more
Open source core with closed source clustering available either on-premise or on...
» more
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