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DBMS > Apache Impala vs. FatDB vs. GridDB vs. OpenQM

System Properties Comparison Apache Impala vs. FatDB vs. GridDB vs. OpenQM

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Editorial information provided by DB-Engines
NameApache Impala  Xexclude from comparisonFatDB  Xexclude from comparisonGridDB  Xexclude from comparisonOpenQM infoalso called QM  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.Scalable in-memory time series database optimized for IoT and Big DataQpenQM is a high-performance, self-tuning, multi-value DBMS
Primary database modelRelational DBMSDocument store
Key-value store
Time Series DBMSMultivalue DBMS
Secondary database modelsDocument storeKey-value store
Relational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score13.77
Rank#40  Overall
#24  Relational DBMS
Score1.95
Rank#128  Overall
#10  Time Series DBMS
Score0.27
Rank#298  Overall
#10  Multivalue DBMS
Websiteimpala.apache.orggriddb.netwww.rocketsoftware.com/­products/­rocket-multivalue-application-development-platform/­rocket-open-qm
Technical documentationimpala.apache.org/­impala-docs.htmldocs.griddb.net
DeveloperApache Software Foundation infoApache top-level project, originally developed by ClouderaFatCloudToshiba CorporationRocket Software, originally Martin Phillips
Initial release2013201220131993
Current release4.1.0, June 20225.1, August 20223.4-12
License infoCommercial or Open SourceOpen Source infoApache Version 2commercialOpen Source infoAGPL version 3 and Apache License, version 2.0 , commercial license (standard and advanced editions) also availableOpen Source infoGPLv2, extended commercial license available
Cloud-based only infoOnly available as a cloud servicenononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC++C#C++
Server operating systemsLinuxWindowsLinuxAIX
FreeBSD
Linux
macOS
Raspberry Pi
Solaris
Windows
Data schemeyesschema-freeyesyes infowith some exceptions
Typing infopredefined data types such as float or dateyesyesyes infonumerical, string, blob, geometry, boolean, timestamp
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.nonoyes
Secondary indexesyesyesyesyes
SQL infoSupport of SQLSQL-like DML and DDL statementsno infoVia inetgration in SQL ServerSQL92, SQL-like TQL (Toshiba Query Language)no
APIs and other access methodsJDBC
ODBC
.NET Client API
LINQ
RESTful HTTP API
RPC
Windows WCF Bindings
JDBC
ODBC
Proprietary protocol
RESTful HTTP/JSON API
Supported programming languagesAll languages supporting JDBC/ODBCC#C
C++
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
Ruby
.Net
Basic
C
Java
Objective C
PHP
Python
Server-side scripts infoStored proceduresyes infouser defined functions and integration of map-reduceyes infovia applicationsnoyes
Triggersnoyes infovia applicationsyesyes
Partitioning methods infoMethods for storing different data on different nodesShardingShardingShardingyes
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication factorselectable replication factorSource-replica replicationyes
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes infoquery execution via MapReduceyesConnector for using GridDB as an input source and output destination for Hadoop MapReduce jobsno
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual ConsistencyEventual Consistency
Immediate Consistency
Immediate consistency within container, eventual consistency across containersImmediate Consistency
Foreign keys infoReferential integritynononono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanonoACID at container levelACID
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.noyes
User concepts infoAccess controlAccess rights for users, groups and roles infobased on Apache Sentry and Kerberosno infoCan implement custom security layer via applicationsAccess rights for users can be defined per databaseAccess rights can be defined down to the item level
More information provided by the system vendor
Apache ImpalaFatDBGridDBOpenQM infoalso called QM
Specific characteristicsGridDB is a highly scalable, in-memory time series database optimized for IoT and...
» more
Competitive advantages1. Optimized for IoT Equipped with Toshiba's proprietary key-container data model...
» more
Typical application scenariosFactory IoT, Automative Industry, Energy, BEMS, Smart Community, Monitoring system.
» more
Key customersDenso International [see use case ] An Electric Power company [see use case ] Ishinomaki...
» more
Market metricsGitHub trending repository
» more
Licensing and pricing modelsOpen Source license (AGPL v3 & Apache v2) Commercial license (subscription)
» more

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More resources
Apache ImpalaFatDBGridDBOpenQM infoalso called QM
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