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DBMS > Apache Impala vs. FatDB vs. GigaSpaces vs. Kinetica

System Properties Comparison Apache Impala vs. FatDB vs. GigaSpaces vs. Kinetica

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Editorial information provided by DB-Engines
NameApache Impala  Xexclude from comparisonFatDB  Xexclude from comparisonGigaSpaces  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.
DescriptionAnalytic DBMS for HadoopA .NET NoSQL DBMS that can integrate with and extend SQL Server.High performance in-memory data grid platform, powering three products: Smart Cache, Smart ODS (Operational Data Store), Smart Augmented TransactionsFully vectorized database across both GPUs and CPUs
Primary database modelRelational DBMSDocument store
Key-value store
Document store
Object oriented DBMS infoValues are user defined objects
Relational DBMS
Secondary database modelsDocument storeGraph DBMS
Search engine
Spatial DBMS
Time Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score13.77
Rank#40  Overall
#24  Relational DBMS
Score0.97
Rank#192  Overall
#32  Document stores
#6  Object oriented DBMS
Score0.64
Rank#236  Overall
#109  Relational DBMS
Websiteimpala.apache.orgwww.gigaspaces.comwww.kinetica.com
Technical documentationimpala.apache.org/­impala-docs.htmldocs.gigaspaces.com/­latest/­landing.htmldocs.kinetica.com
DeveloperApache Software Foundation infoApache top-level project, originally developed by ClouderaFatCloudGigaspaces TechnologiesKinetica
Initial release2013201220002012
Current release4.1.0, June 202215.5, September 20207.1, August 2021
License infoCommercial or Open SourceOpen Source infoApache Version 2commercialOpen Source infoApache Version 2; Commercial licenses availablecommercial
Cloud-based only infoOnly available as a cloud servicenononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC++C#Java, C++, .NetC, C++
Server operating systemsLinuxWindowsLinux
macOS
Solaris
Windows
Linux
Data schemeyesschema-freeschema-freeyes
Typing infopredefined data types such as float or dateyesyesyesyes
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 infoXML can be used for describing objects metadatano
Secondary indexesyesyesyesyes
SQL infoSupport of SQLSQL-like DML and DDL statementsno infoVia inetgration in SQL ServerSQL-99 for query and DML statementsSQL-like DML and DDL statements
APIs and other access methodsJDBC
ODBC
.NET Client API
LINQ
RESTful HTTP API
RPC
Windows WCF Bindings
GigaSpaces LRMI
Hibernate
JCache
JDBC
JPA
ODBC
RESTful HTTP API
Spring Data
JDBC
ODBC
RESTful HTTP API
Supported programming languagesAll languages supporting JDBC/ODBCC#.Net
C++
Java
Python
Scala
C++
Java
JavaScript (Node.js)
Python
Server-side scripts infoStored proceduresyes infouser defined functions and integration of map-reduceyes infovia applicationsyesuser defined functions
Triggersnoyes infovia applicationsyes, event driven architectureyes infotriggers when inserted values for one or more columns fall within a specified range
Partitioning methods infoMethods for storing different data on different nodesShardingShardingShardingSharding
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication factorselectable replication factorMulti-source replication infosynchronous or asynchronous
Source-replica replication infosynchronous or asynchronous
Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes infoquery execution via MapReduceyesyes infoMap-Reduce pattern can be built with XAP task executorsno
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual ConsistencyEventual Consistency
Immediate Consistency
Immediate Consistency infoConsistency level configurable: ALL, QUORUM, ANYImmediate Consistency or Eventual Consistency depending on configuration
Foreign keys infoReferential integritynononoyes
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.noyesyes infoGPU vRAM or System RAM
User concepts infoAccess controlAccess rights for users, groups and roles infobased on Apache Sentry and Kerberosno infoCan implement custom security layer via applicationsRole-based access controlAccess rights for users and roles on table level

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More resources
Apache ImpalaFatDBGigaSpacesKinetica
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