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DBMS > Apache Impala vs. GeoMesa vs. GridDB vs. RethinkDB

System Properties Comparison Apache Impala vs. GeoMesa vs. GridDB vs. RethinkDB

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Editorial information provided by DB-Engines
NameApache Impala  Xexclude from comparisonGeoMesa  Xexclude from comparisonGridDB  Xexclude from comparisonRethinkDB  Xexclude from comparison
DescriptionAnalytic DBMS for HadoopGeoMesa is a distributed spatio-temporal DBMS based on various systems as storage layer.Scalable in-memory time series database optimized for IoT and Big DataDBMS for the Web with a mechanism to push updated query results to applications in realtime.
Primary database modelRelational DBMSSpatial DBMSTime Series DBMSDocument store
Secondary database modelsDocument storeKey-value store
Relational DBMS
Spatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score12.45
Rank#40  Overall
#24  Relational DBMS
Score0.86
Rank#205  Overall
#4  Spatial DBMS
Score2.09
Rank#120  Overall
#10  Time Series DBMS
Score2.66
Rank#107  Overall
#20  Document stores
Websiteimpala.apache.orgwww.geomesa.orggriddb.netrethinkdb.com
Technical documentationimpala.apache.org/­impala-docs.htmlwww.geomesa.org/­documentation/­stable/­user/­index.htmldocs.griddb.netrethinkdb.com/­docs
DeveloperApache Software Foundation infoApache top-level project, originally developed by ClouderaCCRi and othersToshiba CorporationThe Linux Foundation infosince July 2017
Initial release2013201420132009
Current release4.1.0, June 20225.0.0, May 20245.1, August 20222.4.1, August 2020
License infoCommercial or Open SourceOpen Source infoApache Version 2Open Source infoApache License 2.0Open Source infoAGPL version 3 and Apache License, version 2.0 , commercial license (standard and advanced editions) also availableOpen Source infoApache Version 2
Cloud-based only infoOnly available as a cloud servicenononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC++ScalaC++C++
Server operating systemsLinuxLinuxLinux
OS X
Windows
Data schemeyesyesyesschema-free
Typing infopredefined data types such as float or dateyesyesyes infonumerical, string, blob, geometry, boolean, timestampyes infostring, binary, float, bool, date, geometry
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.nononono
Secondary indexesyesyesyesyes
SQL infoSupport of SQLSQL-like DML and DDL statementsnoSQL92, SQL-like TQL (Toshiba Query Language)no
APIs and other access methodsJDBC
ODBC
JDBC
ODBC
Proprietary protocol
RESTful HTTP/JSON API
Supported programming languagesAll languages supporting JDBC/ODBCC
C++
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
Ruby
C infocommunity-supported driver
C# infocommunity-supported driver
C++ infocommunity-supported driver
Clojure infocommunity-supported driver
Dart infocommunity-supported driver
Erlang infocommunity-supported driver
Go infocommunity-supported driver
Haskell infocommunity-supported driver
Java infoofficial driver
JavaScript (Node.js) infoofficial driver
Lisp infocommunity-supported driver
Lua infocommunity-supported driver
Objective-C infocommunity-supported driver
Perl infocommunity-supported driver
PHP infocommunity-supported driver
Python infoofficial driver
Ruby infoofficial driver
Scala infocommunity-supported driver
Server-side scripts infoStored proceduresyes infouser defined functions and integration of map-reducenono
TriggersnonoyesClient-side triggers through changefeeds
Partitioning methods infoMethods for storing different data on different nodesShardingdepending on storage layerShardingSharding inforange based
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication factordepending on storage layerSource-replica replicationSource-replica replication
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 jobsyes
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual Consistencydepending on storage layerImmediate 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 levelAtomic single-document operations
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes infoMVCC based
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.nodepending on storage layeryesno
User concepts infoAccess controlAccess rights for users, groups and roles infobased on Apache Sentry and Kerberosyes infodepending on the DBMS used for storageAccess rights for users can be defined per databaseyes infousers and table-level permissions
More information provided by the system vendor
Apache ImpalaGeoMesaGridDBRethinkDB
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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Apache ImpalaGeoMesaGridDBRethinkDB
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