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DBMS > Faircom DB vs. FatDB vs. Hive vs. Kinetica

System Properties Comparison Faircom DB vs. FatDB vs. Hive vs. Kinetica

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Editorial information provided by DB-Engines
NameFaircom DB infoformerly c-treeACE  Xexclude from comparisonFatDB  Xexclude from comparisonHive  Xexclude from comparisonKinetica  Xexclude from comparison
FatDB/FatCloud has ceased operations as a company with February 2014. FatDB is discontinued and excluded from the ranking.
DescriptionNative high-speed multi-model DBMS for relational and key-value store data simultaneously accessible through SQL and NoSQL APIs.A .NET NoSQL DBMS that can integrate with and extend SQL Server.data warehouse software for querying and managing large distributed datasets, built on HadoopFully vectorized database across both GPUs and CPUs
Primary database modelKey-value store
Relational DBMS
Document store
Key-value store
Relational DBMSRelational DBMS
Secondary database modelsSpatial DBMS
Time Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.29
Rank#304  Overall
#43  Key-value stores
#136  Relational DBMS
Score59.76
Rank#18  Overall
#12  Relational DBMS
Score0.66
Rank#234  Overall
#107  Relational DBMS
Websitewww.faircom.com/­products/­faircom-dbhive.apache.orgwww.kinetica.com
Technical documentationdocs.faircom.com/­docs/­en/­UUID-7446ae34-a1a7-c843-c894-d5322e395184.htmlcwiki.apache.org/­confluence/­display/­Hive/­Homedocs.kinetica.com
DeveloperFairCom CorporationFatCloudApache Software Foundation infoinitially developed by FacebookKinetica
Initial release1979201220122012
Current releaseV12, November 20203.1.3, April 20227.1, August 2021
License infoCommercial or Open Sourcecommercial infoRestricted, free version availablecommercialOpen Source infoApache Version 2commercial
Cloud-based only infoOnly available as a cloud servicenononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageANSI C, C++C#JavaC, C++
Server operating systemsAIX
FreeBSD
HP-UX
Linux
NetBSD
OS X
QNX
SCO
Solaris
VxWorks
Windows infoeasily portable to other OSs
WindowsAll OS with a Java VMLinux
Data schemeschema free, schema optional, schema required, partial schema,schema-freeyesyes
Typing infopredefined data types such as float or dateyes, ANSI SQL Types, JSON, typed binary structuresyesyesyes
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 indexesyesyesyesyes
SQL infoSupport of SQLyes, ANSI SQL with proprietary extensionsno infoVia inetgration in SQL ServerSQL-like DML and DDL statementsSQL-like DML and DDL statements
APIs and other access methodsADO.NET
Direct SQL
JDBC
JPA
ODBC
RESTful HTTP/JSON API
RESTful MQTT/JSON API
RPC
.NET Client API
LINQ
RESTful HTTP API
RPC
Windows WCF Bindings
JDBC
ODBC
Thrift
JDBC
ODBC
RESTful HTTP API
Supported programming languages.Net
C
C#
C++
Java
JavaScript (Node.js and browser)
PHP
Python
Visual Basic
C#C++
Java
PHP
Python
C++
Java
JavaScript (Node.js)
Python
Server-side scripts infoStored proceduresyes info.Net, JavaScript, C/C++yes infovia applicationsyes infouser defined functions and integration of map-reduceuser defined functions
Triggersyesyes infovia applicationsnoyes infotriggers when inserted values for one or more columns fall within a specified range
Partitioning methods infoMethods for storing different data on different nodesFile partitioning, horizontal partitioning, sharding infoCustomizable business rules for table partitioningShardingShardingSharding
Replication methods infoMethods for redundantly storing data on multiple nodesyes, configurable to be parallel or serial, synchronous or asynchronous, uni-directional or bi-directional, ACID-consistent or eventually consistent (with custom conflict resolution).selectable replication factorselectable replication factorSource-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyesyes infoquery execution via MapReduceno
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual Consistency
Immediate Consistency
Tunable consistency per server, database, table, and transaction
Eventual Consistency
Immediate Consistency
Eventual ConsistencyImmediate Consistency or Eventual Consistency depending on configuration
Foreign keys infoReferential integrityyesnonoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datatunable from ACID to Eventually Consistentnonono
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentYes, tunable from durable to delayed durability to in-memoryyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesyes infoGPU vRAM or System RAM
User concepts infoAccess controlFine grained access rights according to SQL-standard with additional protections for filesno infoCan implement custom security layer via applicationsAccess rights for users, groups and rolesAccess rights for users and roles on table level

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More resources
Faircom DB infoformerly c-treeACEFatDBHiveKinetica
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