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DBMS > Amazon Redshift vs. Databricks vs. MarkLogic

System Properties Comparison Amazon Redshift vs. Databricks vs. MarkLogic

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Editorial information provided by DB-Engines
NameAmazon Redshift  Xexclude from comparisonDatabricks  Xexclude from comparisonMarkLogic  Xexclude from comparison
DescriptionLarge scale data warehouse service for use with business intelligence toolsThe 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.Operational and transactional Enterprise NoSQL database
Primary database modelRelational DBMSDocument store
Relational DBMS
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
Score14.70
Rank#36  Overall
#22  Relational DBMS
Score102.66
Rank#12  Overall
#2  Document stores
#8  Relational DBMS
Score4.24
Rank#64  Overall
#11  Document stores
#1  Native XML DBMS
#1  RDF stores
#8  Search engines
Websiteaws.amazon.com/­redshiftwww.databricks.comwww.progress.com/­marklogic
Technical documentationdocs.aws.amazon.com/­redshiftdocs.databricks.comwww.progress.com/­marklogic/­documentation
DeveloperAmazon (based on PostgreSQL)DatabricksMarkLogic Corp.
Initial release201220132001
Current release11.0, December 2022
License infoCommercial or Open Sourcecommercialcommercialcommercial inforestricted free version is available
Cloud-based only infoOnly available as a cloud serviceyesyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageCC++
Server operating systemshostedhostedLinux
OS X
Windows
Data schemeyesFlexible Schema (defined schema, partial schema, schema free)schema-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.noyesyes
Secondary indexesrestrictedyesyes
SQL infoSupport of SQLyes infodoes not fully support an SQL-standardwith Databricks SQLyes infoSQL92
APIs and other access methodsJDBC
ODBC
JDBC
ODBC
RESTful HTTP API
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 languagesAll languages supporting JDBC/ODBCPython
R
Scala
C
C#
C++
Java
JavaScript (Node.js)
Perl
PHP
Python
Ruby
Server-side scripts infoStored proceduresuser defined functions infoin Pythonuser defined functions and aggregatesyes infovia XQuery or JavaScript
Triggersnoyes
Partitioning methods infoMethods for storing different data on different nodesShardingSharding
Replication methods infoMethods for redundantly storing data on multiple nodesyesyesyes
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyes infovia Hadoop Connector, HDFS Direct Access and in-database MapReduce jobs
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integrityyes infoinformational only, not enforced by the systemno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACIDACID 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.yesnoyes, with Range Indexes
User concepts infoAccess controlfine grained access rights according to SQL-standardRole-based access control at the document and subdocument levels

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More resources
Amazon RedshiftDatabricksMarkLogic
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