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DBMS > Databricks vs. FatDB vs. HBase vs. Sequoiadb vs. Teradata Aster

System Properties Comparison Databricks vs. FatDB vs. HBase vs. Sequoiadb vs. Teradata Aster

Editorial information provided by DB-Engines
NameDatabricks  Xexclude from comparisonFatDB  Xexclude from comparisonHBase  Xexclude from comparisonSequoiadb  Xexclude from comparisonTeradata Aster  Xexclude from comparison
FatDB/FatCloud has ceased operations as a company with February 2014. FatDB is discontinued and excluded from the ranking.Teradata Aster has been integrated into other Teradata systems and therefore will be removed from the DB-Engines 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 BigTableNewSQL database with distributed OLTP and SQLPlatform for big data analytics on multistructured data sources and types
Primary database modelDocument store
Relational DBMS
Document store
Key-value store
Wide column storeDocument store
Relational DBMS
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
Score0.45
Rank#261  Overall
#41  Document stores
#122  Relational DBMS
Websitewww.databricks.comhbase.apache.orgwww.sequoiadb.com
Technical documentationdocs.databricks.comhbase.apache.org/­book.htmlwww.sequoiadb.com/­en/­index.php?m=Files&a=index
DeveloperDatabricksFatCloudApache Software Foundation infoApache top-level project, originally developed by PowersetSequoiadb Ltd.Teradata
Initial release20132012200820132005
Current release2.3.4, January 2021
License infoCommercial or Open SourcecommercialcommercialOpen Source infoApache version 2Open Source infoServer: AGPL; Client: Apache V2commercial
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 systemshostedWindowsLinux
Unix
Windows infousing Cygwin
LinuxLinux
Data schemeFlexible Schema (defined schema, partial schema, schema free)schema-freeschema-free, schema definition possibleschema-freeFlexible Schema (defined schema, partial schema, schema free) infodefined schema within the relational store; partial schema or schema free in the Aster File Store
Typing infopredefined data types such as float or dateyesoptions to bring your own types, AVROyes infooid, date, timestamp, binary, regexyes
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.yesnonoyes infoin Aster File Store
Secondary indexesyesyesnoyesyes
SQL infoSupport of SQLwith Databricks SQLno infoVia inetgration in SQL ServernoSQL-like query languageyes
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
proprietary protocol using JSONADO.NET
JDBC
ODBC
OLE DB
Supported programming languagesPython
R
Scala
C#C
C#
C++
Groovy
Java
PHP
Python
Scala
.Net
C++
Java
PHP
Python
C
C#
C++
Java
Python
R
Server-side scripts infoStored proceduresuser defined functions and aggregatesyes infovia applicationsyes infoCoprocessors in JavaJavaScriptR packages
Triggersyes infovia applicationsyesnono
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
Source-replica replicationyes infoDimension tables are replicated across all nodes in the cluster. The number of replicas for the file store can be configured.
MapReduce infoOffers an API for user-defined Map/Reduce methodsyesyesnoyes infoSQL Map-Reduce Framework
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyEventual Consistency
Immediate Consistency
Immediate Consistency or Eventual ConsistencyEventual ConsistencyImmediate Consistency or Eventual Consistency depending on configuration
Foreign keys infoReferential integritynononono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDnoSingle row ACID (across millions of columns)Document is locked during a transactionACID
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.noyesnono
User concepts infoAccess controlno infoCan implement custom security layer via applicationsAccess Control Lists (ACL) for RBAC, integration with Apache Ranger for RBAC & ABACsimple password-based access controlfine grained access rights according to SQL-standard
More information provided by the system vendor
DatabricksFatDBHBaseSequoiadbTeradata Aster
Specific characteristicsSupported database models : In addition to the Document store and Relational DBMS...
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More resources
DatabricksFatDBHBaseSequoiadbTeradata Aster
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