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DBMS > FatDB vs. Hive vs. IRONdb vs. Kinetica vs. Transbase

System Properties Comparison FatDB vs. Hive vs. IRONdb vs. Kinetica vs. Transbase

Editorial information provided by DB-Engines
NameFatDB  Xexclude from comparisonHive  Xexclude from comparisonIRONdb  Xexclude from comparisonKinetica  Xexclude from comparisonTransbase  Xexclude from comparison
FatDB/FatCloud has ceased operations as a company with February 2014. FatDB is discontinued and excluded from the ranking.IRONdb seems to be discontinued. Therefore it is excluded from the DB-Engines Ranking.
DescriptionA .NET NoSQL DBMS that can integrate with and extend SQL Server.data warehouse software for querying and managing large distributed datasets, built on HadoopA distributed Time Series DBMS with a focus on scalability, fault tolerance and operational simplicityFully vectorized database across both GPUs and CPUsA resource-optimized, high-performance, universally applicable RDBMS
Primary database modelDocument store
Key-value store
Relational DBMSTime Series DBMSRelational DBMSRelational DBMS
Secondary database modelsSpatial DBMS
Time Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score61.17
Rank#18  Overall
#12  Relational DBMS
Score0.64
Rank#236  Overall
#109  Relational DBMS
Score0.11
Rank#341  Overall
#150  Relational DBMS
Websitehive.apache.orgwww.circonus.com/solutions/time-series-database/www.kinetica.comwww.transaction.de/­en/­products/­transbase.html
Technical documentationcwiki.apache.org/­confluence/­display/­Hive/­Homedocs.circonus.com/irondb/category/getting-starteddocs.kinetica.comwww.transaction.de/­en/­products/­transbase/­features.html
DeveloperFatCloudApache Software Foundation infoinitially developed by FacebookCirconus LLC.KineticaTransaction Software GmbH
Initial release20122012201720121987
Current release3.1.3, April 2022V0.10.20, January 20187.1, August 2021Transbase 8.3, 2022
License infoCommercial or Open SourcecommercialOpen Source infoApache Version 2commercialcommercialcommercial infofree development license
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#JavaC and C++C, C++C and C++
Server operating systemsWindowsAll OS with a Java VMLinuxLinuxFreeBSD
Linux
macOS
Solaris
Windows
Data schemeschema-freeyesschema-freeyesyes
Typing infopredefined data types such as float or dateyesyesyes infotext, numeric, histogramsyesyes
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.nonono
Secondary indexesyesyesnoyesyes
SQL infoSupport of SQLno infoVia inetgration in SQL ServerSQL-like DML and DDL statementsSQL-like query language (Circonus Analytics Query Language: CAQL)SQL-like DML and DDL statementsyes
APIs and other access methods.NET Client API
LINQ
RESTful HTTP API
RPC
Windows WCF Bindings
JDBC
ODBC
Thrift
HTTP APIJDBC
ODBC
RESTful HTTP API
ADO.NET
JDBC
ODBC
Proprietary native API
Supported programming languagesC#C++
Java
PHP
Python
.Net
C
C++
Clojure
Erlang
Go
Haskell
Java
JavaScript
JavaScript (Node.js)
Lisp
Lua
Perl
PHP
Python
R
Ruby
Rust
Scala
C++
Java
JavaScript (Node.js)
Python
C
C#
C++
Java
JavaScript
Kotlin
Objective-C
PHP
Python
Server-side scripts infoStored proceduresyes infovia applicationsyes infouser defined functions and integration of map-reduceyes, in Luauser defined functionsyes
Triggersyes infovia applicationsnonoyes infotriggers when inserted values for one or more columns fall within a specified rangeyes
Partitioning methods infoMethods for storing different data on different nodesShardingShardingAutomatic, metric affinity per nodeSharding
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication factorselectable replication factorconfigurable replication factor, datacenter awareSource-replica replicationSource-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsyesyes infoquery execution via MapReducenonono
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual Consistency
Immediate Consistency
Eventual ConsistencyImmediate consistency per node, eventual consistency across nodesImmediate Consistency or Eventual Consistency depending on configurationImmediate Consistency
Foreign keys infoReferential integritynononoyesyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanonononoyes
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
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.noyes infoGPU vRAM or System RAMno
User concepts infoAccess controlno infoCan implement custom security layer via applicationsAccess rights for users, groups and rolesnoAccess rights for users and roles on table levelfine grained access rights according to SQL-standard

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More resources
FatDBHiveIRONdbKineticaTransbase
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