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DBMS > Drizzle vs. Heroic vs. Kdb vs. Kinetica vs. Sphinx

System Properties Comparison Drizzle vs. Heroic vs. Kdb vs. Kinetica vs. Sphinx

Editorial information provided by DB-Engines
NameDrizzle  Xexclude from comparisonHeroic  Xexclude from comparisonKdb  Xexclude from comparisonKinetica  Xexclude from comparisonSphinx  Xexclude from comparison
Drizzle has published its last release in September 2012. The open-source project is discontinued and Drizzle is excluded from the DB-Engines ranking.
DescriptionMySQL fork with a pluggable micro-kernel and with an emphasis of performance over compatibility.Time Series DBMS built at Spotify based on Cassandra or Google Cloud Bigtable, and ElasticSearchHigh performance Time Series DBMSFully vectorized database across both GPUs and CPUsOpen source search engine for searching in data from different sources, e.g. relational databases
Primary database modelRelational DBMSTime Series DBMSTime Series DBMS
Vector DBMS
Relational DBMSSearch engine
Secondary database modelsRelational DBMSSpatial DBMS
Time Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.46
Rank#265  Overall
#22  Time Series DBMS
Score7.71
Rank#49  Overall
#2  Time Series DBMS
#1  Vector DBMS
Score0.66
Rank#234  Overall
#107  Relational DBMS
Score5.95
Rank#55  Overall
#5  Search engines
Websitegithub.com/­spotify/­heroickx.comwww.kinetica.comsphinxsearch.com
Technical documentationspotify.github.io/­heroiccode.kx.comdocs.kinetica.comsphinxsearch.com/­docs
DeveloperDrizzle project, originally started by Brian AkerSpotifyKx Systems, a division of First Derivatives plcKineticaSphinx Technologies Inc.
Initial release200820142000 infokdb was released 2000, kdb+ in 200320122001
Current release7.2.4, September 20123.6, May 20187.1, August 20213.5.1, February 2023
License infoCommercial or Open SourceOpen Source infoGNU GPLOpen Source infoApache 2.0commercial infofree 32-bit versioncommercialOpen Source infoGPL version 2, commercial licence available
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++JavaqC, C++C++
Server operating systemsFreeBSD
Linux
OS X
Linux
OS X
Solaris
Windows
LinuxFreeBSD
Linux
NetBSD
OS X
Solaris
Windows
Data schemeyesschema-freeyesyesyes
Typing infopredefined data types such as float or dateyesyesyesyesno
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.noyesno
Secondary indexesyesyes infovia Elasticsearchyes infotable attribute 'grouped'yesyes infofull-text index on all search fields
SQL infoSupport of SQLyes infowith proprietary extensionsnoSQL-like query language (q)SQL-like DML and DDL statementsSQL-like query language (SphinxQL)
APIs and other access methodsJDBCHQL (Heroic Query Language, a JSON-based language)
HTTP API
HTTP API
JDBC
Jupyter
Kafka
ODBC
WebSocket
JDBC
ODBC
RESTful HTTP API
Proprietary protocol
Supported programming languagesC
C++
Java
PHP
C
C#
C++
Go
J
Java
JavaScript
Lua
MatLab
Perl
PHP
Python
R
Scala
C++
Java
JavaScript (Node.js)
Python
C++ infounofficial client library
Java
Perl infounofficial client library
PHP
Python
Ruby infounofficial client library
Server-side scripts infoStored proceduresnonouser defined functionsuser defined functionsno
Triggersno infohooks for callbacks inside the server can be used.noyes 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 nodesShardingShardinghorizontal partitioningShardingSharding infoPartitioning is done manually, search queries against distributed index is supported
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication
Source-replica replication
yesSource-replica replicationSource-replica replicationnone
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonono infosimilar paradigm used for internal processingnono
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual Consistency
Immediate Consistency
Immediate ConsistencyImmediate Consistency or Eventual Consistency depending on configuration
Foreign keys infoReferential integrityyesnoyesyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDnononono
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
Durability infoSupport for making data persistentyesyesyesyesyes infoThe original contents of fields are not stored in the Sphinx 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 controlPluggable authentication mechanisms infoe.g. LDAP, HTTPrights management via user accountsAccess rights for users and roles on table levelno
More information provided by the system vendor
DrizzleHeroicKdbKineticaSphinx
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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DrizzleHeroicKdbKineticaSphinx
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