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DBMS > Apache Phoenix vs. BigObject vs. Kdb vs. MySQL

System Properties Comparison Apache Phoenix vs. BigObject vs. Kdb vs. MySQL

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Editorial information provided by DB-Engines
NameApache Phoenix  Xexclude from comparisonBigObject  Xexclude from comparisonKdb  Xexclude from comparisonMySQL  Xexclude from comparison
DescriptionA scale-out RDBMS with evolutionary schema built on Apache HBaseAnalytic DBMS for real-time computations and queriesHigh performance Time Series DBMSWidely used open source RDBMS
Primary database modelRelational DBMSRelational DBMS infoa hierachical model (tree) can be imposedTime Series DBMS
Vector DBMS
Relational DBMS infoKey/Value like access via memcached API
Secondary database modelsRelational DBMSDocument store
Spatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.97
Rank#126  Overall
#59  Relational DBMS
Score0.13
Rank#333  Overall
#147  Relational DBMS
Score7.55
Rank#53  Overall
#3  Time Series DBMS
#1  Vector DBMS
Score1083.74
Rank#2  Overall
#2  Relational DBMS
Websitephoenix.apache.orgbigobject.iokx.comwww.mysql.com
Technical documentationphoenix.apache.orgdocs.bigobject.iocode.kx.comdev.mysql.com/­doc
DeveloperApache Software FoundationBigObject, Inc.Kx Systems, a division of First Derivatives plcOracle infosince 2010, originally MySQL AB, then Sun
Initial release201420152000 infokdb was released 2000, kdb+ in 20031995
Current release5.0-HBase2, July 2018 and 4.15-HBase1, December 20193.6, May 20188.3.0, January 2024
License infoCommercial or Open SourceOpen Source infoApache Version 2.0commercial infofree community edition availablecommercial infofree 32-bit versionOpen Source infoGPL version 2. Commercial licenses with extended functionallity are available
Cloud-based only infoOnly available as a cloud servicenononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Aiven for MySQL: Fully managed MySQL, deployable in the cloud of your choice, with seamless integrations and lightning-fast setup.
Implementation languageJavaqC and C++
Server operating systemsLinux
Unix
Windows
Linux infodistributed as a docker-image
OS X infodistributed as a docker-image (boot2docker)
Windows infodistributed as a docker-image (boot2docker)
Linux
OS X
Solaris
Windows
FreeBSD
Linux
OS X
Solaris
Windows
Data schemeyes infolate-bound, schema-on-read capabilitiesyesyesyes
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.nonoyesyes
Secondary indexesyesyesyes infotable attribute 'grouped'yes
SQL infoSupport of SQLyesSQL-like DML and DDL statementsSQL-like query language (q)yes infowith proprietary extensions
APIs and other access methodsJDBCfluentd
ODBC
RESTful HTTP API
HTTP API
JDBC
Jupyter
Kafka
ODBC
WebSocket
ADO.NET
JDBC
ODBC
Proprietary native API
Supported programming languagesC
C#
C++
Go
Groovy
Java
PHP
Python
Scala
C
C#
C++
Go
J
Java
JavaScript
Lua
MatLab
Perl
PHP
Python
R
Scala
Ada
C
C#
C++
D
Delphi
Eiffel
Erlang
Haskell
Java
JavaScript (Node.js)
Objective-C
OCaml
Perl
PHP
Python
Ruby
Scheme
Tcl
Server-side scripts infoStored proceduresuser defined functionsLuauser defined functionsyes infoproprietary syntax
Triggersnonoyes infowith viewsyes
Partitioning methods infoMethods for storing different data on different nodesShardingnonehorizontal partitioninghorizontal partitioning, sharding with MySQL Cluster or MySQL Fabric
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication
Source-replica replication
noneSource-replica replicationMulti-source replication
Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsHadoop integrationnono infosimilar paradigm used for internal processingno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate Consistency or Eventual ConsistencynoneImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integritynoyes infoautomatically between fact table and dimension tablesyesyes infonot for MyISAM storage engine
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDnonoACID infonot for MyISAM storage engine
Concurrency infoSupport for concurrent manipulation of datayesyes infoRead/write lock on objects (tables, trees)yesyes infotable locks or row locks depending on storage engine
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.yesyesyesyes
User concepts infoAccess controlAccess Control Lists (using HBase ACL) for RBAC, integration with Apache Ranger for RBAC & ABAC, multi-tenancynorights management via user accountsUsers with fine-grained authorization concept infono user groups or roles
More information provided by the system vendor
Apache PhoenixBigObjectKdbMySQL
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 PhoenixBigObjectKdbMySQL
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