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DBMS > Apache Druid vs. Apache Impala vs. Kdb vs. Linter

System Properties Comparison Apache Druid vs. Apache Impala vs. Kdb vs. Linter

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Editorial information provided by DB-Engines
NameApache Druid  Xexclude from comparisonApache Impala  Xexclude from comparisonKdb  Xexclude from comparisonLinter  Xexclude from comparison
DescriptionOpen-source analytics data store designed for sub-second OLAP queries on high dimensionality and high cardinality dataAnalytic DBMS for HadoopHigh performance Time Series DBMSRDBMS for high security requirements
Primary database modelRelational DBMS
Time Series DBMS
Relational DBMSTime Series DBMS
Vector DBMS
Relational DBMS
Secondary database modelsDocument storeRelational DBMSSpatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score3.25
Rank#90  Overall
#47  Relational DBMS
#7  Time Series DBMS
Score12.45
Rank#40  Overall
#24  Relational DBMS
Score7.71
Rank#49  Overall
#2  Time Series DBMS
#1  Vector DBMS
Score0.12
Rank#350  Overall
#152  Relational DBMS
Websitedruid.apache.orgimpala.apache.orgkx.comlinter.ru
Technical documentationdruid.apache.org/­docs/­latest/­designimpala.apache.org/­impala-docs.htmlcode.kx.com
DeveloperApache Software Foundation and contributorsApache Software Foundation infoApache top-level project, originally developed by ClouderaKx Systems, a division of First Derivatives plcrelex.ru
Initial release201220132000 infokdb was released 2000, kdb+ in 20031990
Current release29.0.1, April 20244.1.0, June 20223.6, May 2018
License infoCommercial or Open SourceOpen Source infoApache license v2Open Source infoApache Version 2commercial infofree 32-bit versioncommercial
Cloud-based only infoOnly available as a cloud servicenononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaC++qC and C++
Server operating systemsLinux
OS X
Unix
LinuxLinux
OS X
Solaris
Windows
AIX
Android
BSD
HP Open VMS
iOS
Linux
OS X
VxWorks
Windows
Data schemeyes infoschema-less columns are supportedyesyesyes
Typing infopredefined data types such as float or dateyesyesyesyes
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 indexesyesyesyes infotable attribute 'grouped'yes
SQL infoSupport of SQLSQL for queryingSQL-like DML and DDL statementsSQL-like query language (q)yes
APIs and other access methodsJDBC
RESTful HTTP/JSON API
JDBC
ODBC
HTTP API
JDBC
Jupyter
Kafka
ODBC
WebSocket
ADO.NET
JDBC
LINQ
ODBC
OLE DB
Oracle Call Interface (OCI)
Supported programming languagesClojure
JavaScript
PHP
Python
R
Ruby
Scala
All languages supporting JDBC/ODBCC
C#
C++
Go
J
Java
JavaScript
Lua
MatLab
Perl
PHP
Python
R
Scala
C
C#
C++
Java
Perl
PHP
Python
Qt
Ruby
Tcl
Server-side scripts infoStored proceduresnoyes infouser defined functions and integration of map-reduceuser defined functionsyes infoproprietary syntax with the possibility to convert from PL/SQL
Triggersnonoyes infowith viewsyes
Partitioning methods infoMethods for storing different data on different nodesSharding infomanual/auto, time-basedShardinghorizontal partitioningnone
Replication methods infoMethods for redundantly storing data on multiple nodesyes, via HDFS, S3 or other storage enginesselectable replication factorSource-replica replicationSource-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyes infoquery execution via MapReduceno infosimilar paradigm used for internal processingno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyEventual ConsistencyImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integritynonoyesyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanononoACID
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.nonoyes
User concepts infoAccess controlRBAC using LDAP or Druid internals for users and groups for read/write by datasource and systemAccess rights for users, groups and roles infobased on Apache Sentry and Kerberosrights management via user accountsfine grained access rights according to SQL-standard
More information provided by the system vendor
Apache DruidApache ImpalaKdbLinter
Specific characteristicsIntegrated columnar database & programming system for streaming, real time and historical...
» more
Competitive advantagesprovides seamless scalability; runs on industry standard server platforms; is top-ranked...
» more
Typical application scenariostick database streaming sensor data massive intelligence applications oil and gas...
» more
Key customersGoldman Sachs Morgan Stanley Merrill Lynch J.P. Morgan Deutsche Bank IEX Securities...
» more
Market metricskdb+ performance and reliability proven by our customers in critical infrastructure...
» more
Licensing and pricing modelsupon request
» more

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More resources
Apache DruidApache ImpalaKdbLinter
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