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DBMS > Apache Impala vs. Elasticsearch vs. Kdb vs. Spark SQL vs. VictoriaMetrics

System Properties Comparison Apache Impala vs. Elasticsearch vs. Kdb vs. Spark SQL vs. VictoriaMetrics

Editorial information provided by DB-Engines
NameApache Impala  Xexclude from comparisonElasticsearch  Xexclude from comparisonKdb  Xexclude from comparisonSpark SQL  Xexclude from comparisonVictoriaMetrics  Xexclude from comparison
DescriptionAnalytic DBMS for HadoopA distributed, RESTful modern search and analytics engine based on Apache Lucene infoElasticsearch lets you perform and combine many types of searches such as structured, unstructured, geo, and metricHigh performance Time Series DBMSSpark SQL is a component on top of 'Spark Core' for structured data processingA fast, cost-effective and scalable Time Series DBMS and monitoring solution
Primary database modelRelational DBMSSearch engineTime Series DBMS
Vector DBMS
Relational DBMSTime Series DBMS
Secondary database modelsDocument storeDocument store
Spatial DBMS
Vector DBMS
Relational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score12.45
Rank#40  Overall
#24  Relational DBMS
Score132.83
Rank#7  Overall
#1  Search engines
Score7.71
Rank#49  Overall
#2  Time Series DBMS
#1  Vector DBMS
Score18.04
Rank#33  Overall
#20  Relational DBMS
Score1.23
Rank#172  Overall
#15  Time Series DBMS
Websiteimpala.apache.orgwww.elastic.co/­elasticsearchkx.comspark.apache.org/­sqlvictoriametrics.com
Technical documentationimpala.apache.org/­impala-docs.htmlwww.elastic.co/­guide/­en/­elasticsearch/­reference/­current/­index.htmlcode.kx.comspark.apache.org/­docs/­latest/­sql-programming-guide.htmldocs.victoriametrics.com
github.com/­VictoriaMetrics/­VictoriaMetrics/­wiki
DeveloperApache Software Foundation infoApache top-level project, originally developed by ClouderaElasticKx Systems, a division of First Derivatives plcApache Software FoundationVictoriaMetrics
Initial release201320102000 infokdb was released 2000, kdb+ in 200320142018
Current release4.1.0, June 20228.6, January 20233.6, May 20183.5.0 ( 2.13), September 2023v1.91, May 2023
License infoCommercial or Open SourceOpen Source infoApache Version 2Open Source infoElastic Licensecommercial infofree 32-bit versionOpen Source infoApache 2.0Open Source infoApache Version 2.0
Cloud-based only infoOnly available as a cloud servicenonononono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageC++JavaqScalaGo
Server operating systemsLinuxAll OS with a Java VMLinux
OS X
Solaris
Windows
Linux
OS X
Windows
FreeBSD
Linux
macOS
OpenBSD
Data schemeyesschema-free infoFlexible type definitions. Once a type is defined, it is persistentyesyes
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.nonoyesnono
Secondary indexesyesyes infoAll search fields are automatically indexedyes infotable attribute 'grouped'no
SQL infoSupport of SQLSQL-like DML and DDL statementsSQL-like query languageSQL-like query language (q)SQL-like DML and DDL statementsno
APIs and other access methodsJDBC
ODBC
Java API
RESTful HTTP/JSON API
HTTP API
JDBC
Jupyter
Kafka
ODBC
WebSocket
JDBC
ODBC
Graphite protocol
InfluxDB Line Protocol
OpenTSDB
Prometheus Query API
Prometheus Remote Read/Write
Supported programming languagesAll languages supporting JDBC/ODBC.Net
Groovy
Community Contributed Clients
Java
JavaScript
Perl
PHP
Python
Ruby
C
C#
C++
Go
J
Java
JavaScript
Lua
MatLab
Perl
PHP
Python
R
Scala
Java
Python
R
Scala
Server-side scripts infoStored proceduresyes infouser defined functions and integration of map-reduceyesuser defined functionsnono
Triggersnoyes infoby using the 'percolation' featureyes infowith viewsnono
Partitioning methods infoMethods for storing different data on different nodesShardingShardinghorizontal partitioningyes, utilizing Spark Core
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication factoryesSource-replica replicationnoneSynchronous replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes infoquery execution via MapReduceES-Hadoop Connectorno infosimilar paradigm used for internal processingno
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual ConsistencyEventual Consistency infoSynchronous doc based replication. Get by ID may show delays up to 1 sec. Configurable write consistency: one, quorum, allImmediate ConsistencyEventual Consistency
Foreign keys infoReferential integritynonoyesnono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanonononono
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
Durability infoSupport for making data persistentyesyesyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noMemcached and Redis integrationyesnono
User concepts infoAccess controlAccess rights for users, groups and roles infobased on Apache Sentry and Kerberosrights management via user accountsno
More information provided by the system vendor
Apache ImpalaElasticsearchKdbSpark SQLVictoriaMetrics
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 ImpalaElasticsearchKdbSpark SQLVictoriaMetrics
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