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DBMS > Databricks vs. FatDB vs. HBase vs. Microsoft Azure Table Storage vs. Yaacomo

System Properties Comparison Databricks vs. FatDB vs. HBase vs. Microsoft Azure Table Storage vs. Yaacomo

Editorial information provided by DB-Engines
NameDatabricks  Xexclude from comparisonFatDB  Xexclude from comparisonHBase  Xexclude from comparisonMicrosoft Azure Table Storage  Xexclude from comparisonYaacomo  Xexclude from comparison
FatDB/FatCloud has ceased operations as a company with February 2014. FatDB is discontinued and excluded from the ranking.Yaacomo seems to be discontinued and is 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 BigTableA Wide Column Store for rapid development using massive semi-structured datasetsOpenCL based in-memory RDBMS, designed for efficiently utilizing the hardware via parallel computing
Primary database modelDocument store
Relational DBMS
Document store
Key-value store
Wide column storeWide column storeRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score81.08
Rank#15  Overall
#2  Document stores
#10  Relational DBMS
Score27.97
Rank#26  Overall
#2  Wide column stores
Score4.04
Rank#77  Overall
#6  Wide column stores
Websitewww.databricks.comhbase.apache.orgazure.microsoft.com/­en-us/­services/­storage/­tablesyaacomo.com
Technical documentationdocs.databricks.comhbase.apache.org/­book.html
DeveloperDatabricksFatCloudApache Software Foundation infoApache top-level project, originally developed by PowersetMicrosoftQ2WEB GmbH
Initial release20132012200820122009
Current release2.3.4, January 2021
License infoCommercial or Open SourcecommercialcommercialOpen Source infoApache version 2commercialcommercial
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#Java
Server operating systemshostedWindowsLinux
Unix
Windows infousing Cygwin
hostedAndroid
Linux
Windows
Data schemeFlexible Schema (defined schema, partial schema, schema free)schema-freeschema-free, schema definition possibleschema-freeyes
Typing infopredefined data types such as float or dateyesoptions to bring your own types, AVROyesyes
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 indexesyesyesnonoyes
SQL infoSupport of SQLwith Databricks SQLno infoVia inetgration in SQL Servernonoyes
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 APIJDBC
ODBC
Supported programming languagesPython
R
Scala
C#C
C#
C++
Groovy
Java
PHP
Python
Scala
.Net
C#
C++
Java
JavaScript (Node.js)
PHP
Python
Ruby
Server-side scripts infoStored proceduresuser defined functions and aggregatesyes infovia applicationsyes infoCoprocessors in Javano
Triggersyes infovia applicationsyesnoyes
Partitioning methods infoMethods for storing different data on different nodesShardingShardingSharding infoImplicit feature of the cloud servicehorizontal partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesyesselectable replication factorMulti-source replication
Source-replica replication
yes infoimplicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsyesyesnono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyEventual Consistency
Immediate Consistency
Immediate Consistency or Eventual ConsistencyImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integritynononoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDnoSingle row ACID (across millions of columns)optimistic lockingACID
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.noyesnoyes
User concepts infoAccess controlno infoCan implement custom security layer via applicationsAccess Control Lists (ACL) for RBAC, integration with Apache Ranger for RBAC & ABACAccess rights based on private key authentication or shared access signaturesfine grained access rights according to SQL-standard
More information provided by the system vendor
DatabricksFatDBHBaseMicrosoft Azure Table StorageYaacomo
Specific characteristicsSupported database models : In addition to the Document store and Relational DBMS...
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More resources
DatabricksFatDBHBaseMicrosoft Azure Table StorageYaacomo
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