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DBMS > Databricks vs. FatDB vs. HBase vs. IBM Cloudant vs. Sequoiadb

System Properties Comparison Databricks vs. FatDB vs. HBase vs. IBM Cloudant vs. Sequoiadb

Editorial information provided by DB-Engines
NameDatabricks  Xexclude from comparisonFatDB  Xexclude from comparisonHBase  Xexclude from comparisonIBM Cloudant  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 BigTableDatabase as a Service offering based on Apache CouchDBNewSQL database with distributed OLTP and SQL
Primary database modelDocument store
Relational DBMS
Document store
Key-value store
Wide column storeDocument storeDocument store
Relational 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
Score2.68
Rank#106  Overall
#20  Document stores
Score0.45
Rank#261  Overall
#41  Document stores
#122  Relational DBMS
Websitewww.databricks.comhbase.apache.orgwww.ibm.com/­products/­cloudantwww.sequoiadb.com
Technical documentationdocs.databricks.comhbase.apache.org/­book.htmlcloud.ibm.com/­docs/­Cloudantwww.sequoiadb.com/­en/­index.php?m=Files&a=index
DeveloperDatabricksFatCloudApache Software Foundation infoApache top-level project, originally developed by PowersetIBM, Apache Software Foundation infoIBM acquired Cloudant in February 2014Sequoiadb Ltd.
Initial release20132012200820102013
Current release2.3.4, January 2021
License infoCommercial or Open SourcecommercialcommercialOpen Source infoApache version 2commercialOpen Source infoServer: AGPL; Client: Apache V2
Cloud-based only infoOnly available as a cloud serviceyesnonoyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageC#JavaErlangC++
Server operating systemshostedWindowsLinux
Unix
Windows infousing Cygwin
hostedLinux
Data schemeFlexible Schema (defined schema, partial schema, schema free)schema-freeschema-free, schema definition possibleschema-freeschema-free
Typing infopredefined data types such as float or dateyesoptions to bring your own types, AVROnoyes 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.yesnonono
Secondary indexesyesyesnoyesyes
SQL infoSupport of SQLwith Databricks SQLno infoVia inetgration in SQL ServernonoSQL-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
RESTful HTTP/JSON APIproprietary protocol using JSON
Supported programming languagesPython
R
Scala
C#C
C#
C++
Groovy
Java
PHP
Python
Scala
C#
Java
JavaScript
Objective-C
PHP
Ruby
.Net
C++
Java
PHP
Python
Server-side scripts infoStored proceduresuser defined functions and aggregatesyes infovia applicationsyes infoCoprocessors in JavaView functions (Map-Reduce) in JavaScriptJavaScript
Triggersyes infovia applicationsyesyesno
Partitioning methods infoMethods for storing different data on different nodesShardingShardingShardingSharding
Replication methods infoMethods for redundantly storing data on multiple nodesyesselectable replication factorMulti-source replication
Source-replica replication
Multi-source replication
Source-replica replication
Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsyesyesyesno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyEventual Consistency
Immediate Consistency
Immediate Consistency or Eventual ConsistencyEventual ConsistencyEventual Consistency
Foreign keys infoReferential integritynononono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDnoSingle row ACID (across millions of columns)no infoatomic operations within a document possibleDocument is locked during a transaction
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes infoOptimistic lockingyes
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.noyesnono
User concepts infoAccess controlno infoCan implement custom security layer via applicationsAccess Control Lists (ACL) for RBAC, integration with Apache Ranger for RBAC & ABACAccess rights for users can be defined per databasesimple password-based access control
More information provided by the system vendor
DatabricksFatDBHBaseIBM CloudantSequoiadb
Specific characteristicsSupported database models : In addition to the Document store and Relational DBMS...
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DatabricksFatDBHBaseIBM CloudantSequoiadb
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