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DBMS > Apache Phoenix vs. DataFS vs. Kdb vs. Solr

System Properties Comparison Apache Phoenix vs. DataFS vs. Kdb vs. Solr

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Editorial information provided by DB-Engines
NameApache Phoenix  Xexclude from comparisonDataFS  Xexclude from comparisonKdb  Xexclude from comparisonSolr  Xexclude from comparison
DescriptionA scale-out RDBMS with evolutionary schema built on Apache HBaseAll data is stored inside objects which are linked by so-called link attributes. Objects consist of classes which can be extended and de-extended at runtime. Graphs can be defined with a struct.High performance Time Series DBMSA widely used distributed, scalable search engine based on Apache Lucene
Primary database modelRelational DBMSObject oriented DBMSTime Series DBMS
Vector DBMS
Search engine
Secondary database modelsGraph DBMSRelational DBMSSpatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score2.06
Rank#123  Overall
#58  Relational DBMS
Score0.09
Rank#360  Overall
#17  Object oriented DBMS
Score7.71
Rank#49  Overall
#2  Time Series DBMS
#1  Vector DBMS
Score41.02
Rank#24  Overall
#3  Search engines
Websitephoenix.apache.orgnewdatabase.comkx.comsolr.apache.org
Technical documentationphoenix.apache.orgdev.mobiland.com/­Overview.xspcode.kx.comsolr.apache.org/­resources.html
DeveloperApache Software FoundationMobiland AGKx Systems, a division of First Derivatives plcApache Software Foundation
Initial release201420182000 infokdb was released 2000, kdb+ in 20032006
Current release5.0-HBase2, July 2018 and 4.15-HBase1, December 20191.1.263, October 20223.6, May 20189.6.1, May 2024
License infoCommercial or Open SourceOpen Source infoApache Version 2.0commercialcommercial infofree 32-bit versionOpen 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 languageJavaqJava
Server operating systemsLinux
Unix
Windows
WindowsLinux
OS X
Solaris
Windows
All OS with a Java VM inforuns as a servlet in servlet container (e.g. Tomcat, Jetty is included)
Data schemeyes infolate-bound, schema-on-read capabilitiesClasses, Structs, and Lists are written in proprietary DataTypeDefinitionLanguage (.dtdl) and Objects consisting of those are written in proprietary DataAccessDefinitionLanguage (.dadl)yesyes 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.nonoyesyes
Secondary indexesyesnoyes infotable attribute 'grouped'yes infoAll search fields are automatically indexed
SQL infoSupport of SQLyesnoSQL-like query language (q)Solr Parallel SQL Interface
APIs and other access methodsJDBC.NET Client API
Proprietary client DLL
WinRT client
HTTP API
JDBC
Jupyter
Kafka
ODBC
WebSocket
Java API
RESTful HTTP/JSON API
Supported programming languagesC
C#
C++
Go
Groovy
Java
PHP
Python
Scala
.Net
C
C#
C++
VB.Net
C
C#
C++
Go
J
Java
JavaScript
Lua
MatLab
Perl
PHP
Python
R
Scala
.Net
Erlang
Java
JavaScript
any language that supports sockets and either XML or JSON
Perl
PHP
Python
Ruby
Scala
Server-side scripts infoStored proceduresuser defined functionsuser defined functionsJava plugins
Triggersnono, except callback-events from server when changes happenedyes infowith viewsyes infoUser configurable commands triggered on index changes
Partitioning methods infoMethods for storing different data on different nodesShardingProprietary Sharding systemhorizontal partitioningSharding
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication
Source-replica replication
Source-replica replicationyes
MapReduce infoOffers an API for user-defined Map/Reduce methodsHadoop integrationnono infosimilar paradigm used for internal processingspark-solr: github.com/­lucidworks/­spark-solr and streaming expressions to reduce
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate Consistency or Eventual ConsistencyImmediate ConsistencyImmediate ConsistencyEventual Consistency
Foreign keys infoReferential integritynoyesyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACIDnooptimistic 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.yesnoyesyes
User concepts infoAccess controlAccess Control Lists (using HBase ACL) for RBAC, integration with Apache Ranger for RBAC & ABAC, multi-tenancyWindows-Profilerights management via user accountsyes
More information provided by the system vendor
Apache PhoenixDataFSKdbSolr
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 PhoenixDataFSKdbSolr
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