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DBMS > Apache Druid vs. eXtremeDB vs. Kinetica vs. Postgres-XL

System Properties Comparison Apache Druid vs. eXtremeDB vs. Kinetica vs. Postgres-XL

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Editorial information provided by DB-Engines
NameApache Druid  Xexclude from comparisoneXtremeDB  Xexclude from comparisonKinetica  Xexclude from comparisonPostgres-XL  Xexclude from comparison
DescriptionOpen-source analytics data store designed for sub-second OLAP queries on high dimensionality and high cardinality dataNatively in-memory DBMS with options for persistency, high-availability and clusteringFully vectorized database across both GPUs and CPUsBased on PostgreSQL enhanced with MPP and write-scale-out cluster features
Primary database modelRelational DBMS
Time Series DBMS
Relational DBMS
Time Series DBMS
Relational DBMSRelational DBMS
Secondary database modelsSpatial DBMS
Time Series DBMS
Document store
Spatial DBMS
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
Score0.74
Rank#223  Overall
#103  Relational DBMS
#18  Time Series DBMS
Score0.64
Rank#236  Overall
#109  Relational DBMS
Score0.49
Rank#256  Overall
#117  Relational DBMS
Websitedruid.apache.orgwww.mcobject.comwww.kinetica.comwww.postgres-xl.org
Technical documentationdruid.apache.org/­docs/­latest/­designwww.mcobject.com/­docs/­extremedb.htmdocs.kinetica.comwww.postgres-xl.org/­documentation
DeveloperApache Software Foundation and contributorsMcObjectKinetica
Initial release2012200120122014 infosince 2012, originally named StormDB
Current release29.0.1, April 20248.2, 20217.1, August 202110 R1, October 2018
License infoCommercial or Open SourceOpen Source infoApache license v2commercialcommercialOpen Source infoMozilla public license
Cloud-based only infoOnly available as a cloud servicenononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaC and C++C, C++C
Server operating systemsLinux
OS X
Unix
AIX
HP-UX
Linux
macOS
Solaris
Windows
LinuxLinux
macOS
Data schemeyes infoschema-less columns are supportedyesyesyes
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.nono infosupport of XML interfaces availablenoyes infoXML type, but no XML query functionality
Secondary indexesyesyesyesyes
SQL infoSupport of SQLSQL for queryingyes infowith the option: eXtremeSQLSQL-like DML and DDL statementsyes infodistributed, parallel query execution
APIs and other access methodsJDBC
RESTful HTTP/JSON API
.NET Client API
JDBC
JNI
ODBC
Proprietary protocol
RESTful HTTP API
JDBC
ODBC
RESTful HTTP API
ADO.NET
JDBC
native C library
ODBC
streaming API for large objects
Supported programming languagesClojure
JavaScript
PHP
Python
R
Ruby
Scala
.Net
C
C#
C++
Java
Lua
Python
Scala
C++
Java
JavaScript (Node.js)
Python
.Net
C
C++
Delphi
Erlang
Java
JavaScript (Node.js)
Perl
PHP
Python
Tcl
Server-side scripts infoStored proceduresnoyesuser defined functionsuser defined functions
Triggersnoyes infoby defining eventsyes infotriggers when inserted values for one or more columns fall within a specified rangeyes
Partitioning methods infoMethods for storing different data on different nodesSharding infomanual/auto, time-basedhorizontal partitioning / shardingShardinghorizontal partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesyes, via HDFS, S3 or other storage enginesActive Replication Fabric™ for IoT
Multi-source replication infoby means of eXtremeDB Cluster option
Source-replica replication infoby means of eXtremeDB High Availability option
Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnononono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyImmediate Consistency or Eventual Consistency depending on configurationImmediate Consistency
Foreign keys infoReferential integritynoyesyesyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACIDnoACID infoMVCC
Concurrency infoSupport for concurrent manipulation of datayesyes infoOptimistic (MVCC) and pessimistic (locking) strategies availableyesyes
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.noyesyes infoGPU vRAM or System RAMno
User concepts infoAccess controlRBAC using LDAP or Druid internals for users and groups for read/write by datasource and systemAccess rights for users and roles on table levelfine grained access rights according to SQL-standard
More information provided by the system vendor
Apache DruideXtremeDBKineticaPostgres-XL
Specific characteristicseXtremeDB is an in-memory and/or persistent database system that offers an ultra-small...
» more
Competitive advantageseXtremeDB databases can be modeled relationally or as objects and can utilize SQL...
» more
Typical application scenariosIoT application across all markets: Industrial Control, Netcom, Telecom, Defense,...
» more
Key customersSchneider Electronics, F5 Networks, TNS, Boeing, Northrop Grumman, GoPro, ViaSat,...
» more
Market metricsWith hundreds of customers and over 30 million devices/applications using the product...
» more
Licensing and pricing modelsFor server use cases, there is a simple per-server license irrespective of the number...
» more

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More resources
Apache DruideXtremeDBKineticaPostgres-XL
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