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DBMS > Apache Druid vs. Kdb vs. Kinetica vs. Manticore Search

System Properties Comparison Apache Druid vs. Kdb vs. Kinetica vs. Manticore Search

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Editorial information provided by DB-Engines
NameApache Druid  Xexclude from comparisonKdb  Xexclude from comparisonKinetica  Xexclude from comparisonManticore Search  Xexclude from comparison
DescriptionOpen-source analytics data store designed for sub-second OLAP queries on high dimensionality and high cardinality dataHigh performance Time Series DBMSFully vectorized database across both GPUs and CPUsMulti-storage database for search, including full-text search.
Primary database modelRelational DBMS
Time Series DBMS
Time Series DBMS
Vector DBMS
Relational DBMSSearch engine
Secondary database modelsRelational DBMSSpatial DBMS
Time Series DBMS
Time Series DBMS infousing the Manticore Columnar Library
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score3.34
Rank#88  Overall
#48  Relational DBMS
#7  Time Series DBMS
Score7.55
Rank#53  Overall
#3  Time Series DBMS
#1  Vector DBMS
Score0.64
Rank#236  Overall
#109  Relational DBMS
Score0.22
Rank#312  Overall
#21  Search engines
Websitedruid.apache.orgkx.comwww.kinetica.commanticoresearch.com
Technical documentationdruid.apache.org/­docs/­latest/­designcode.kx.comdocs.kinetica.commanual.manticoresearch.com
DeveloperApache Software Foundation and contributorsKx Systems, a division of First Derivatives plcKineticaManticore Software
Initial release20122000 infokdb was released 2000, kdb+ in 200320122017
Current release29.0.1, April 20243.6, May 20187.1, August 20216.0, February 2023
License infoCommercial or Open SourceOpen Source infoApache license v2commercial infofree 32-bit versioncommercialOpen Source infoGPL version 2
Cloud-based only infoOnly available as a cloud servicenononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaqC, C++C++
Server operating systemsLinux
OS X
Unix
Linux
OS X
Solaris
Windows
LinuxFreeBSD
Linux
macOS
Windows
Data schemeyes infoschema-less columns are supportedyesyesFixed schema
Typing infopredefined data types such as float or dateyesyesyesInt, Bigint, Float, Timestamp, Bit, Int array, Bigint array, JSON, Boolean
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.noyesnoCan index from XML
Secondary indexesyesyes infotable attribute 'grouped'yesyes infofull-text index on all search fields
SQL infoSupport of SQLSQL for queryingSQL-like query language (q)SQL-like DML and DDL statementsSQL-like query language
APIs and other access methodsJDBC
RESTful HTTP/JSON API
HTTP API
JDBC
Jupyter
Kafka
ODBC
WebSocket
JDBC
ODBC
RESTful HTTP API
Binary API
RESTful HTTP/JSON API
RESTful HTTP/SQL API
SQL over MySQL
Supported programming languagesClojure
JavaScript
PHP
Python
R
Ruby
Scala
C
C#
C++
Go
J
Java
JavaScript
Lua
MatLab
Perl
PHP
Python
R
Scala
C++
Java
JavaScript (Node.js)
Python
Elixir
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
Server-side scripts infoStored proceduresnouser defined functionsuser defined functionsuser defined functions
Triggersnoyes infowith viewsyes infotriggers when inserted values for one or more columns fall within a specified rangeno
Partitioning methods infoMethods for storing different data on different nodesSharding infomanual/auto, time-basedhorizontal partitioningShardingSharding infoPartitioning is done manually, search queries against distributed index is supported
Replication methods infoMethods for redundantly storing data on multiple nodesyes, via HDFS, S3 or other storage enginesSource-replica replicationSource-replica replicationSynchronous replication based on Galera library
MapReduce infoOffers an API for user-defined Map/Reduce methodsnono infosimilar paradigm used for internal processingnono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyImmediate Consistency or Eventual Consistency depending on configuration
Foreign keys infoReferential integritynoyesyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanononoyes infoisolated transactions for atomic changes and binary logging for safe writes
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyesyesyes infoThe original contents of fields are not stored in the Manticore index.
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyesyes infoGPU vRAM or System RAM
User concepts infoAccess controlRBAC using LDAP or Druid internals for users and groups for read/write by datasource and systemrights management via user accountsAccess rights for users and roles on table levelno
More information provided by the system vendor
Apache DruidKdbKineticaManticore Search
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 DruidKdbKineticaManticore Search
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