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DBMS > Databricks vs. FatDB vs. HBase vs. Kdb vs. Sequoiadb

System Properties Comparison Databricks vs. FatDB vs. HBase vs. Kdb vs. Sequoiadb

Editorial information provided by DB-Engines
NameDatabricks  Xexclude from comparisonFatDB  Xexclude from comparisonHBase  Xexclude from comparisonKdb  Xexclude from comparisonSequoiadb  Xexclude from comparison
FatDB/FatCloud has ceased operations as a company with February 2014. FatDB is discontinued and excluded from the ranking.
DescriptionThe Databricks Lakehouse Platform combines elements of data lakes and data warehouses to provide a unified view onto structured and unstructured data. It is based on Apache Spark.A .NET NoSQL DBMS that can integrate with and extend SQL Server.Wide-column store based on Apache Hadoop and on concepts of BigTableHigh performance Time Series DBMSNewSQL database with distributed OLTP and SQL
Primary database modelDocument store
Relational DBMS
Document store
Key-value store
Wide column storeTime Series DBMS
Vector DBMS
Document store
Relational DBMS
Secondary database modelsRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score78.61
Rank#15  Overall
#2  Document stores
#10  Relational DBMS
Score30.50
Rank#26  Overall
#2  Wide column stores
Score7.55
Rank#53  Overall
#3  Time Series DBMS
#1  Vector DBMS
Score0.45
Rank#261  Overall
#41  Document stores
#122  Relational DBMS
Websitewww.databricks.comhbase.apache.orgkx.comwww.sequoiadb.com
Technical documentationdocs.databricks.comhbase.apache.org/­book.htmlcode.kx.comwww.sequoiadb.com/­en/­index.php?m=Files&a=index
DeveloperDatabricksFatCloudApache Software Foundation infoApache top-level project, originally developed by PowersetKx Systems, a division of First Derivatives plcSequoiadb Ltd.
Initial release2013201220082000 infokdb was released 2000, kdb+ in 20032013
Current release2.3.4, January 20213.6, May 2018
License infoCommercial or Open SourcecommercialcommercialOpen Source infoApache version 2commercial infofree 32-bit versionOpen Source infoServer: AGPL; Client: Apache V2
Cloud-based only infoOnly available as a cloud serviceyesnononono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageC#JavaqC++
Server operating systemshostedWindowsLinux
Unix
Windows infousing Cygwin
Linux
OS X
Solaris
Windows
Linux
Data schemeFlexible Schema (defined schema, partial schema, schema free)schema-freeschema-free, schema definition possibleyesschema-free
Typing infopredefined data types such as float or dateyesoptions to bring your own types, AVROyesyes infooid, date, timestamp, binary, regex
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.yesnoyesno
Secondary indexesyesyesnoyes infotable attribute 'grouped'yes
SQL infoSupport of SQLwith Databricks SQLno infoVia inetgration in SQL ServernoSQL-like query language (q)SQL-like query language
APIs and other access methodsJDBC
ODBC
RESTful HTTP API
.NET Client API
LINQ
RESTful HTTP API
RPC
Windows WCF Bindings
Java API
RESTful HTTP API
Thrift
HTTP API
JDBC
Jupyter
Kafka
ODBC
WebSocket
proprietary protocol using JSON
Supported programming languagesPython
R
Scala
C#C
C#
C++
Groovy
Java
PHP
Python
Scala
C
C#
C++
Go
J
Java
JavaScript
Lua
MatLab
Perl
PHP
Python
R
Scala
.Net
C++
Java
PHP
Python
Server-side scripts infoStored proceduresuser defined functions and aggregatesyes infovia applicationsyes infoCoprocessors in Javauser defined functionsJavaScript
Triggersyes infovia applicationsyesyes infowith viewsno
Partitioning methods infoMethods for storing different data on different nodesShardingShardinghorizontal partitioningSharding
Replication methods infoMethods for redundantly storing data on multiple nodesyesselectable replication factorMulti-source replication
Source-replica replication
Source-replica replicationSource-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsyesyesno infosimilar paradigm used for internal processingno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyEventual Consistency
Immediate Consistency
Immediate Consistency or Eventual ConsistencyImmediate ConsistencyEventual Consistency
Foreign keys infoReferential integritynonoyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDnoSingle row ACID (across millions of columns)noDocument is locked during a transaction
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
Durability infoSupport for making data persistentyesyesyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyesyesno
User concepts infoAccess controlno infoCan implement custom security layer via applicationsAccess Control Lists (ACL) for RBAC, integration with Apache Ranger for RBAC & ABACrights management via user accountssimple password-based access control
More information provided by the system vendor
DatabricksFatDBHBaseKdbSequoiadb
Specific characteristicsSupported database models : In addition to the Document store and Relational DBMS...
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Integrated columnar database & programming system for streaming, real time and historical...
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Competitive advantagesprovides seamless scalability; runs on industry standard server platforms; is top-ranked...
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Typical application scenariostick database streaming sensor data massive intelligence applications oil and gas...
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Key customersGoldman Sachs Morgan Stanley Merrill Lynch J.P. Morgan Deutsche Bank IEX Securities...
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Market metricskdb+ performance and reliability proven by our customers in critical infrastructure...
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Licensing and pricing modelsupon request
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DatabricksFatDBHBaseKdbSequoiadb
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