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DBMS > Apache Impala vs. GridDB vs. Hive vs. SiteWhere

System Properties Comparison Apache Impala vs. GridDB vs. Hive vs. SiteWhere

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Editorial information provided by DB-Engines
NameApache Impala  Xexclude from comparisonGridDB  Xexclude from comparisonHive  Xexclude from comparisonSiteWhere  Xexclude from comparison
DescriptionAnalytic DBMS for HadoopScalable in-memory time series database optimized for IoT and Big Datadata warehouse software for querying and managing large distributed datasets, built on HadoopM2M integration platform for persisting/querying time series data
Primary database modelRelational DBMSTime Series DBMSRelational DBMSTime Series DBMS
Secondary database modelsDocument storeKey-value store
Relational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score12.45
Rank#40  Overall
#24  Relational DBMS
Score2.09
Rank#120  Overall
#10  Time Series DBMS
Score59.76
Rank#18  Overall
#12  Relational DBMS
Score0.06
Rank#383  Overall
#43  Time Series DBMS
Websiteimpala.apache.orggriddb.nethive.apache.orggithub.com/­sitewhere/­sitewhere
Technical documentationimpala.apache.org/­impala-docs.htmldocs.griddb.netcwiki.apache.org/­confluence/­display/­Hive/­Homesitewhere1.sitewhere.io/­index.html
DeveloperApache Software Foundation infoApache top-level project, originally developed by ClouderaToshiba CorporationApache Software Foundation infoinitially developed by FacebookSiteWhere
Initial release2013201320122010
Current release4.1.0, June 20225.1, August 20223.1.3, April 2022
License infoCommercial or Open SourceOpen Source infoApache Version 2Open Source infoAGPL version 3 and Apache License, version 2.0 , commercial license (standard and advanced editions) also availableOpen Source infoApache Version 2Open Source infoCommon Public Attribution License Version 1.0
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++C++JavaJava
Server operating systemsLinuxLinuxAll OS with a Java VMLinux
OS X
Windows
Data schemeyesyesyespredefined scheme
Typing infopredefined data types such as float or dateyesyes infonumerical, string, blob, geometry, boolean, timestampyesyes
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 indexesyesyesyesno
SQL infoSupport of SQLSQL-like DML and DDL statementsSQL92, SQL-like TQL (Toshiba Query Language)SQL-like DML and DDL statementsno
APIs and other access methodsJDBC
ODBC
JDBC
ODBC
Proprietary protocol
RESTful HTTP/JSON API
JDBC
ODBC
Thrift
HTTP REST
Supported programming languagesAll languages supporting JDBC/ODBCC
C++
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
Ruby
C++
Java
PHP
Python
Server-side scripts infoStored proceduresyes infouser defined functions and integration of map-reducenoyes infouser defined functions and integration of map-reduce
Triggersnoyesno
Partitioning methods infoMethods for storing different data on different nodesShardingShardingShardingSharding infobased on HBase
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication factorSource-replica replicationselectable replication factorselectable replication factor infobased on HBase
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes infoquery execution via MapReduceConnector for using GridDB as an input source and output destination for Hadoop MapReduce jobsyes infoquery execution via MapReduceno
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual ConsistencyImmediate consistency within container, eventual consistency across containersEventual ConsistencyImmediate Consistency
Foreign keys infoReferential integritynononono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACID at container levelnono
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.noyesno
User concepts infoAccess controlAccess rights for users, groups and roles infobased on Apache Sentry and KerberosAccess rights for users can be defined per databaseAccess rights for users, groups and rolesUsers with fine-grained authorization concept
More information provided by the system vendor
Apache ImpalaGridDBHiveSiteWhere
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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and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.

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More resources
Apache ImpalaGridDBHiveSiteWhere
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SiteWhere: An open platform for connected devices
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