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DBMS > Apache Impala vs. GridDB vs. InterSystems Caché vs. IRONdb

System Properties Comparison Apache Impala vs. GridDB vs. InterSystems Caché vs. IRONdb

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Editorial information provided by DB-Engines
NameApache Impala  Xexclude from comparisonGridDB  Xexclude from comparisonInterSystems Caché  Xexclude from comparisonIRONdb  Xexclude from comparison
Caché is a deprecated database engine which is substituted with InterSystems IRIS. It therefore is removed from the DB-Engines Ranking.IRONdb seems to be discontinued. Therefore it is excluded from the DB-Engines Ranking.
DescriptionAnalytic DBMS for HadoopScalable in-memory time series database optimized for IoT and Big DataA multi-model DBMS and application serverA distributed Time Series DBMS with a focus on scalability, fault tolerance and operational simplicity
Primary database modelRelational DBMSTime Series DBMSKey-value store
Object oriented DBMS
Relational DBMS
Time Series DBMS
Secondary database modelsDocument storeKey-value store
Relational DBMS
Document store
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
Websiteimpala.apache.orggriddb.netwww.intersystems.com/­products/­cachewww.circonus.com/solutions/time-series-database/
Technical documentationimpala.apache.org/­impala-docs.htmldocs.griddb.netdocs.intersystems.comdocs.circonus.com/irondb/category/getting-started
DeveloperApache Software Foundation infoApache top-level project, originally developed by ClouderaToshiba CorporationInterSystemsCirconus LLC.
Initial release2013201319972017
Current release4.1.0, June 20225.1, August 20222018.1.4, May 2020V0.10.20, January 2018
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 availablecommercialcommercial
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 and C++
Server operating systemsLinuxLinuxAIX
HP Open VMS
HP-UX
Linux
OS X
Solaris
Windows
Linux
Data schemeyesyesdepending on used data modelschema-free
Typing infopredefined data types such as float or dateyesyes infonumerical, string, blob, geometry, boolean, timestampyesyes infotext, numeric, histograms
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.nonoyesno
Secondary indexesyesyesyesno
SQL infoSupport of SQLSQL-like DML and DDL statementsSQL92, SQL-like TQL (Toshiba Query Language)yesSQL-like query language (Circonus Analytics Query Language: CAQL)
APIs and other access methodsJDBC
ODBC
JDBC
ODBC
Proprietary protocol
RESTful HTTP/JSON API
.NET Client API
JDBC
ODBC
RESTful HTTP API
HTTP API
Supported programming languagesAll languages supporting JDBC/ODBCC
C++
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
Ruby
C#
C++
Java
.Net
C
C++
Clojure
Erlang
Go
Haskell
Java
JavaScript
JavaScript (Node.js)
Lisp
Lua
Perl
PHP
Python
R
Ruby
Rust
Scala
Server-side scripts infoStored proceduresyes infouser defined functions and integration of map-reducenoyesyes, in Lua
Triggersnoyesyesno
Partitioning methods infoMethods for storing different data on different nodesShardingShardingnoneAutomatic, metric affinity per node
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication factorSource-replica replicationSource-replica replicationconfigurable replication factor, datacenter aware
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 jobsnono
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual ConsistencyImmediate consistency within container, eventual consistency across containersImmediate ConsistencyImmediate consistency per node, eventual consistency across nodes
Foreign keys infoReferential integritynonoyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACID at container levelACIDno
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.noyesyesno
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 rolesno
More information provided by the system vendor
Apache ImpalaGridDBInterSystems CachéIRONdb
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 ImpalaGridDBInterSystems CachéIRONdb
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