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DBMS > Databricks vs. Ehcache vs. MarkLogic

System Properties Comparison Databricks vs. Ehcache vs. MarkLogic

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Editorial information provided by DB-Engines
NameDatabricks  Xexclude from comparisonEhcache  Xexclude from comparisonMarkLogic  Xexclude from comparison
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 widely adopted Java cache with tiered storage optionsOperational and transactional Enterprise NoSQL database
Primary database modelDocument store
Relational DBMS
Key-value storeDocument 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
Score78.61
Rank#15  Overall
#2  Document stores
#10  Relational DBMS
Score4.89
Rank#67  Overall
#8  Key-value stores
Score5.92
Rank#58  Overall
#10  Document stores
#1  Native XML DBMS
#1  RDF stores
#6  Search engines
Websitewww.databricks.comwww.ehcache.orgwww.marklogic.com
Technical documentationdocs.databricks.comwww.ehcache.org/­documentationdocs.marklogic.com
DeveloperDatabricksTerracotta Inc, owned by Software AGMarkLogic Corp.
Initial release201320092001
Current release3.10.0, March 202211.0, December 2022
License infoCommercial or Open SourcecommercialOpen Source infoApache Version 2; commercial licenses availablecommercial 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 languageJavaC++
Server operating systemshostedAll OS with a Java VMLinux
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.yesnoyes
Secondary indexesyesnoyes
SQL infoSupport of SQLwith Databricks SQLnoyes infoSQL92
APIs and other access methodsJDBC
ODBC
RESTful HTTP API
JCacheJava 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
JavaC
C#
C++
Java
JavaScript (Node.js)
Perl
PHP
Python
Ruby
Server-side scripts infoStored proceduresuser defined functions and aggregatesnoyes infovia XQuery or JavaScript
Triggersyes infoCache Event Listenersyes
Partitioning methods infoMethods for storing different data on different nodesSharding infoby using Terracotta ServerSharding
Replication methods infoMethods for redundantly storing data on multiple nodesyesyes infoby using Terracotta Serveryes
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 ConsistencyTunable Consistency (Strong, Eventual, Weak)Immediate Consistency
Foreign keys infoReferential integritynono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDyes infosupports JTA and can work as an XA resourceACID infocan act as a resource manager in an XA/JTA transaction
Concurrency infoSupport for concurrent manipulation of datayesyesyes
Durability infoSupport for making data persistentyesyes infousing a tiered cache-storage approachyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyesyes, with Range Indexes
User concepts infoAccess controlnoRole-based access control at the document and subdocument levels
More information provided by the system vendor
DatabricksEhcacheMarkLogic
Specific characteristicsSupported database models : In addition to the Document store and Relational DBMS...
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DatabricksEhcacheMarkLogic
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