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

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

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Editorial information provided by DB-Engines
NameApache Impala  Xexclude from comparisonKdb  Xexclude from comparisonLinter  Xexclude from comparisonSolr  Xexclude from comparison
DescriptionAnalytic DBMS for HadoopHigh performance Time Series DBMSRDBMS for high security requirementsA widely used distributed, scalable search engine based on Apache Lucene
Primary database modelRelational DBMSTime Series DBMS
Vector DBMS
Relational DBMSSearch engine
Secondary database modelsDocument storeRelational DBMSSpatial DBMSSpatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
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
Score41.02
Rank#24  Overall
#3  Search engines
Websiteimpala.apache.orgkx.comlinter.rusolr.apache.org
Technical documentationimpala.apache.org/­impala-docs.htmlcode.kx.comsolr.apache.org/­resources.html
DeveloperApache Software Foundation infoApache top-level project, originally developed by ClouderaKx Systems, a division of First Derivatives plcrelex.ruApache Software Foundation
Initial release20132000 infokdb was released 2000, kdb+ in 200319902006
Current release4.1.0, June 20223.6, May 20189.6.1, May 2024
License infoCommercial or Open SourceOpen Source infoApache Version 2commercial infofree 32-bit versioncommercialOpen 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++qC and C++Java
Server operating systemsLinuxLinux
OS X
Solaris
Windows
AIX
Android
BSD
HP Open VMS
iOS
Linux
OS X
VxWorks
Windows
All OS with a Java VM inforuns as a servlet in servlet container (e.g. Tomcat, Jetty is included)
Data schemeyesyesyesyes infoDynamic Fields enables on-the-fly addition of new fields
Typing infopredefined data types such as float or dateyesyesyesyes infosupports customizable data types and automatic typing
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.noyesnoyes
Secondary indexesyesyes infotable attribute 'grouped'yesyes infoAll search fields are automatically indexed
SQL infoSupport of SQLSQL-like DML and DDL statementsSQL-like query language (q)yesSolr Parallel SQL Interface
APIs and other access methodsJDBC
ODBC
HTTP API
JDBC
Jupyter
Kafka
ODBC
WebSocket
ADO.NET
JDBC
LINQ
ODBC
OLE DB
Oracle Call Interface (OCI)
Java API
RESTful HTTP/JSON API
Supported programming languagesAll 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
.Net
Erlang
Java
JavaScript
any language that supports sockets and either XML or JSON
Perl
PHP
Python
Ruby
Scala
Server-side scripts infoStored proceduresyes infouser defined functions and integration of map-reduceuser defined functionsyes infoproprietary syntax with the possibility to convert from PL/SQLJava plugins
Triggersnoyes infowith viewsyesyes infoUser configurable commands triggered on index changes
Partitioning methods infoMethods for storing different data on different nodesShardinghorizontal partitioningnoneSharding
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication factorSource-replica replicationSource-replica replicationyes
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes infoquery execution via MapReduceno infosimilar paradigm used for internal processingnospark-solr: github.com/­lucidworks/­spark-solr and streaming expressions to reduce
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual ConsistencyImmediate ConsistencyImmediate ConsistencyEventual Consistency
Foreign keys infoReferential integritynoyesyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanonoACIDoptimistic locking
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
User concepts infoAccess controlAccess rights for users, groups and roles infobased on Apache Sentry and Kerberosrights management via user accountsfine grained access rights according to SQL-standardyes
More information provided by the system vendor
Apache ImpalaKdbLinterSolr
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 ImpalaKdbLinterSolr
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