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DBMS > FatDB vs. Hive vs. Ignite vs. Riak KV

System Properties Comparison FatDB vs. Hive vs. Ignite vs. Riak KV

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Editorial information provided by DB-Engines
NameFatDB  Xexclude from comparisonHive  Xexclude from comparisonIgnite  Xexclude from comparisonRiak KV  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.data warehouse software for querying and managing large distributed datasets, built on HadoopApache Ignite is a memory-centric distributed database, caching, and processing platform for transactional, analytical, and streaming workloads, delivering in-memory speeds at petabyte scale.Distributed, fault tolerant key-value store
Primary database modelDocument store
Key-value store
Relational DBMSKey-value store
Relational DBMS
Key-value store infowith links between data sets and object tags for the creation of secondary indexes
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score61.17
Rank#18  Overall
#12  Relational DBMS
Score3.16
Rank#96  Overall
#15  Key-value stores
#49  Relational DBMS
Score4.10
Rank#82  Overall
#9  Key-value stores
Websitehive.apache.orgignite.apache.org
Technical documentationcwiki.apache.org/­confluence/­display/­Hive/­Homeapacheignite.readme.io/­docswww.tiot.jp/­riak-docs/­riak/­kv/­latest
DeveloperFatCloudApache Software Foundation infoinitially developed by FacebookApache Software FoundationOpenSource, formerly Basho Technologies
Initial release2012201220152009
Current release3.1.3, April 2022Apache Ignite 2.63.2.0, December 2022
License infoCommercial or Open SourcecommercialOpen Source infoApache Version 2Open Source infoApache 2.0Open Source infoApache version 2, commercial enterprise edition
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 languageC#JavaC++, Java, .NetErlang
Server operating systemsWindowsAll OS with a Java VMLinux
OS X
Solaris
Windows
Linux
OS X
Data schemeschema-freeyesyesschema-free
Typing infopredefined data types such as float or dateyesyesyesno
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.yesno
Secondary indexesyesyesyesrestricted
SQL infoSupport of SQLno infoVia inetgration in SQL ServerSQL-like DML and DDL statementsANSI-99 for query and DML statements, subset of DDLno
APIs and other access methods.NET Client API
LINQ
RESTful HTTP API
RPC
Windows WCF Bindings
JDBC
ODBC
Thrift
HDFS API
Hibernate
JCache
JDBC
ODBC
Proprietary protocol
RESTful HTTP API
Spring Data
HTTP API
Native Erlang Interface
Supported programming languagesC#C++
Java
PHP
Python
C#
C++
Java
PHP
Python
Ruby
Scala
C infounofficial client library
C#
C++ infounofficial client library
Clojure infounofficial client library
Dart infounofficial client library
Erlang
Go infounofficial client library
Groovy infounofficial client library
Haskell infounofficial client library
Java
JavaScript infounofficial client library
Lisp infounofficial client library
Perl infounofficial client library
PHP
Python
Ruby
Scala infounofficial client library
Smalltalk infounofficial client library
Server-side scripts infoStored proceduresyes infovia applicationsyes infouser defined functions and integration of map-reduceyes (compute grid and cache interceptors can be used instead)Erlang
Triggersyes infovia applicationsnoyes (cache interceptors and events)yes infopre-commit hooks and post-commit hooks
Partitioning methods infoMethods for storing different data on different nodesShardingShardingShardingSharding infono "single point of failure"
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication factorselectable replication factoryes (replicated cache)selectable replication factor
MapReduce infoOffers an API for user-defined Map/Reduce methodsyesyes infoquery execution via MapReduceyes (compute grid and hadoop accelerator)yes
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual Consistency
Immediate Consistency
Eventual ConsistencyImmediate ConsistencyEventual Consistency
Foreign keys infoReferential integritynononono infolinks between data sets can be stored
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanonoACIDno
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yes
User concepts infoAccess controlno infoCan implement custom security layer via applicationsAccess rights for users, groups and rolesSecurity Hooks for custom implementationsyes, using Riak Security

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