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

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

Editorial information provided by DB-Engines
NameDatabricks  Xexclude from comparisonFatDB  Xexclude from comparisonGreenplum  Xexclude from comparisonHBase  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.Analytic Database platform built on PostgreSQL. Full name is Pivotal Greenplum Database infoA logical database in Greenplum is an array of individual PostgreSQL databases working together to present a single database image.Wide-column store based on Apache Hadoop and on concepts of BigTableNewSQL database with distributed OLTP and SQL
Primary database modelDocument store
Relational DBMS
Document store
Key-value store
Relational DBMSWide column storeDocument store
Relational DBMS
Secondary database modelsDocument store
Spatial 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
Score8.37
Rank#48  Overall
#30  Relational DBMS
Score30.50
Rank#26  Overall
#2  Wide column stores
Score0.45
Rank#261  Overall
#41  Document stores
#122  Relational DBMS
Websitewww.databricks.comgreenplum.orghbase.apache.orgwww.sequoiadb.com
Technical documentationdocs.databricks.comdocs.greenplum.orghbase.apache.org/­book.htmlwww.sequoiadb.com/­en/­index.php?m=Files&a=index
DeveloperDatabricksFatCloudPivotal Software Inc.Apache Software Foundation infoApache top-level project, originally developed by PowersetSequoiadb Ltd.
Initial release20132012200520082013
Current release7.0.0, September 20232.3.4, January 2021
License infoCommercial or Open SourcecommercialcommercialOpen Source infoApache 2.0Open Source infoApache version 2Open 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#JavaC++
Server operating systemshostedWindowsLinuxLinux
Unix
Windows infousing Cygwin
Linux
Data schemeFlexible Schema (defined schema, partial schema, schema free)schema-freeyesschema-free, schema definition possibleschema-free
Typing infopredefined data types such as float or dateyesyesoptions to bring your own types, AVROyes 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.yesyes infosince Version 4.2nono
Secondary indexesyesyesyesnoyes
SQL infoSupport of SQLwith Databricks SQLno infoVia inetgration in SQL ServeryesnoSQL-like query language
APIs and other access methodsJDBC
ODBC
RESTful HTTP API
.NET Client API
LINQ
RESTful HTTP API
RPC
Windows WCF Bindings
JDBC
ODBC
Java API
RESTful HTTP API
Thrift
proprietary protocol using JSON
Supported programming languagesPython
R
Scala
C#C
Java
Perl
Python
R
C
C#
C++
Groovy
Java
PHP
Python
Scala
.Net
C++
Java
PHP
Python
Server-side scripts infoStored proceduresuser defined functions and aggregatesyes infovia applicationsyesyes infoCoprocessors in JavaJavaScript
Triggersyes infovia applicationsyesyesno
Partitioning methods infoMethods for storing different data on different nodesShardingShardingShardingSharding
Replication methods infoMethods for redundantly storing data on multiple nodesyesselectable replication factorSource-replica replicationMulti-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 ConsistencyImmediate Consistency or Eventual ConsistencyEventual Consistency
Foreign keys infoReferential integritynoyesnono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDnoACIDSingle row ACID (across millions of columns)Document 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.nonoyesno
User concepts infoAccess controlno infoCan implement custom security layer via applicationsfine grained access rights according to SQL-standardAccess Control Lists (ACL) for RBAC, integration with Apache Ranger for RBAC & ABACsimple password-based access control
More information provided by the system vendor
DatabricksFatDBGreenplumHBaseSequoiadb
Specific characteristicsSupported database models : In addition to the Document store and Relational DBMS...
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DatabricksFatDBGreenplumHBaseSequoiadb
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