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DBMS > Apache Impala vs. Apache IoTDB vs. InfluxDB vs. Kdb

System Properties Comparison Apache Impala vs. Apache IoTDB vs. InfluxDB vs. Kdb

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Editorial information provided by DB-Engines
NameApache Impala  Xexclude from comparisonApache IoTDB  Xexclude from comparisonInfluxDB  Xexclude from comparisonKdb  Xexclude from comparison
DescriptionAnalytic DBMS for HadoopAn IoT native database with high performance for data management and analysis, deployable on the edge and the cloud and integrated with Hadoop, Spark and FlinkDBMS for storing time series, events and metricsHigh performance Time Series DBMS
Primary database modelRelational DBMSTime Series DBMSTime Series DBMSTime Series DBMS
Vector DBMS
Secondary database modelsDocument storeSpatial DBMS infowith GEO packageRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score12.45
Rank#40  Overall
#24  Relational DBMS
Score1.31
Rank#164  Overall
#14  Time Series DBMS
Score24.39
Rank#28  Overall
#1  Time Series DBMS
Score7.71
Rank#49  Overall
#2  Time Series DBMS
#1  Vector DBMS
Websiteimpala.apache.orgiotdb.apache.orgwww.influxdata.com/­products/­influxdb-overviewkx.com
Technical documentationimpala.apache.org/­impala-docs.htmliotdb.apache.org/­UserGuide/­Master/­QuickStart/­QuickStart.htmldocs.influxdata.com/­influxdbcode.kx.com
DeveloperApache Software Foundation infoApache top-level project, originally developed by ClouderaApache Software FoundationKx Systems, a division of First Derivatives plc
Initial release2013201820132000 infokdb was released 2000, kdb+ in 2003
Current release4.1.0, June 20221.1.0, April 20232.7.6, April 20243.6, May 2018
License infoCommercial or Open SourceOpen Source infoApache Version 2Open Source infoApache Version 2.0Open Source infoMIT-License; commercial enterprise version availablecommercial infofree 32-bit version
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++JavaGoq
Server operating systemsLinuxAll OS with a Java VM (>= 1.8)Linux
OS X infothrough Homebrew
Linux
OS X
Solaris
Windows
Data schemeyesyesschema-freeyes
Typing infopredefined data types such as float or dateyesyesNumeric data and Stringsyes
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.nononoyes
Secondary indexesyesyesnoyes infotable attribute 'grouped'
SQL infoSupport of SQLSQL-like DML and DDL statementsSQL-like query languageSQL-like query languageSQL-like query language (q)
APIs and other access methodsJDBC
ODBC
JDBC
Native API
HTTP API
JSON over UDP
HTTP API
JDBC
Jupyter
Kafka
ODBC
WebSocket
Supported programming languagesAll languages supporting JDBC/ODBCC
C#
C++
Go
Java
Python
Scala
.Net
Clojure
Erlang
Go
Haskell
Java
JavaScript
JavaScript (Node.js)
Lisp
Perl
PHP
Python
R
Ruby
Rust
Scala
C
C#
C++
Go
J
Java
JavaScript
Lua
MatLab
Perl
PHP
Python
R
Scala
Server-side scripts infoStored proceduresyes infouser defined functions and integration of map-reduceyesnouser defined functions
Triggersnoyesnoyes infowith views
Partitioning methods infoMethods for storing different data on different nodesShardinghorizontal partitioning (by time range) + vertical partitioning (by deviceId)Sharding infoin enterprise version onlyhorizontal partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication factorselectable replication methods; using Raft/IoTConsensus algorithm to ensure strong/eventual data consistency among multiple replicasselectable replication factor infoin enterprise version onlySource-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes infoquery execution via MapReduceIntegration with Hadoop and Sparknono infosimilar paradigm used for internal processing
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual ConsistencyEventual Consistency
Strong Consistency with Raft
Immediate Consistency
Foreign keys infoReferential integritynononoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanononono
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 infoDepending on used storage engineyes
User concepts infoAccess controlAccess rights for users, groups and roles infobased on Apache Sentry and Kerberosyessimple rights management via user accountsrights management via user accounts
More information provided by the system vendor
Apache ImpalaApache IoTDBInfluxDBKdb
Specific characteristicsInfluxData is the creator of InfluxDB , the open source time series database. It...
» more
Integrated columnar database & programming system for streaming, real time and historical...
» more
Competitive advantagesTime to Value InfluxDB is available in all the popular languages and frameworks,...
» more
provides seamless scalability; runs on industry standard server platforms; is top-ranked...
» more
Typical application scenariosIoT & Sensor Monitoring Developers are witnessing the instrumentation of every available...
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tick database streaming sensor data massive intelligence applications oil and gas...
» more
Key customersInfluxData has more than 1,900 paying customers, including customers include MuleSoft,...
» more
Goldman Sachs Morgan Stanley Merrill Lynch J.P. Morgan Deutsche Bank IEX Securities...
» more
Market metricsFastest-growing database to drive 27,500 GitHub stars Over 750,000 daily active instances
» more
kdb+ performance and reliability proven by our customers in critical infrastructure...
» more
Licensing and pricing modelsOpen source core with closed source clustering available either on-premise or on...
» more
upon request
» more
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