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DBMS > Databricks vs. FatDB vs. MarkLogic

System Properties Comparison Databricks vs. FatDB vs. MarkLogic

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Editorial information provided by DB-Engines
NameDatabricks  Xexclude from comparisonFatDB  Xexclude from comparisonMarkLogic  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.Operational and transactional Enterprise NoSQL database
Primary database modelDocument store
Relational DBMS
Document store
Key-value store
Document store
Native XML DBMS
RDF store infoas of version 7
Search engine
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score76.33
Rank#17  Overall
#3  Document stores
#11  Relational DBMS
Score6.50
Rank#56  Overall
#10  Document stores
#1  Native XML DBMS
#1  RDF stores
#5  Search engines
Websitewww.databricks.comwww.marklogic.com
Technical documentationdocs.databricks.comdocs.marklogic.com
DeveloperDatabricksFatCloudMarkLogic Corp.
Initial release201320122001
Current release11.0, December 2022
License infoCommercial or Open Sourcecommercialcommercialcommercial inforestricted free version is available
Cloud-based only infoOnly available as a cloud serviceyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC#C++
Server operating systemshostedWindowsLinux
OS X
Windows
Data schemeFlexible Schema (defined schema, partial schema, schema free)schema-freeschema-free infoSchema can be enforced
Typing infopredefined data types such as float or dateyesyes
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
Secondary indexesyesyesyes
SQL infoSupport of SQLwith Databricks SQLno infoVia inetgration in SQL Serveryes infoSQL92
APIs and other access methodsJDBC
ODBC
RESTful HTTP API
.NET Client API
LINQ
RESTful HTTP API
RPC
Windows WCF Bindings
Java API
Node.js Client API
ODBC
proprietary Optic API infoProprietary Query API, introduced with version 9
RESTful HTTP API
SPARQL
WebDAV
XDBC
XQuery
XSLT
Supported programming languagesPython
R
Scala
C#C
C#
C++
Java
JavaScript (Node.js)
Perl
PHP
Python
Ruby
Server-side scripts infoStored proceduresuser defined functions and aggregatesyes infovia applicationsyes infovia XQuery or JavaScript
Triggersyes infovia applicationsyes
Partitioning methods infoMethods for storing different data on different nodesShardingSharding
Replication methods infoMethods for redundantly storing data on multiple nodesyesselectable replication factoryes
MapReduce infoOffers an API for user-defined Map/Reduce methodsyesyes infovia Hadoop Connector, HDFS Direct Access and in-database MapReduce jobs
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyEventual Consistency
Immediate Consistency
Immediate Consistency
Foreign keys infoReferential integritynono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDnoACID infocan act as a resource manager in an XA/JTA transaction
Concurrency infoSupport for concurrent manipulation of datayesyesyes
Durability infoSupport for making data persistentyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyes, with Range Indexes
User concepts infoAccess controlno infoCan implement custom security layer via applicationsRole-based access control at the document and subdocument levels
More information provided by the system vendor
DatabricksFatDBMarkLogic
Specific characteristicsSupported database models : In addition to the Document store and Relational DBMS...
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More resources
DatabricksFatDBMarkLogic
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