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DBMS > Databricks vs. Ehcache vs. MarkLogic vs. Solr

System Properties Comparison Databricks vs. Ehcache vs. MarkLogic vs. Solr

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Editorial information provided by DB-Engines
NameDatabricks  Xexclude from comparisonEhcache  Xexclude from comparisonMarkLogic  Xexclude from comparisonSolr  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 databaseA widely used distributed, scalable search engine based on Apache Lucene
Primary database modelDocument store
Relational DBMS
Key-value storeDocument store
Native XML DBMS
RDF store infoas of version 7
Search engine
Search engine
Secondary database modelsSpatial 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
Score4.64
Rank#68  Overall
#8  Key-value stores
Score5.18
Rank#63  Overall
#11  Document stores
#1  Native XML DBMS
#1  RDF stores
#7  Search engines
Score41.02
Rank#24  Overall
#3  Search engines
Websitewww.databricks.comwww.ehcache.orgwww.progress.com/­marklogicsolr.apache.org
Technical documentationdocs.databricks.comwww.ehcache.org/­documentationwww.progress.com/­marklogic/­documentationsolr.apache.org/­resources.html
DeveloperDatabricksTerracotta Inc, owned by Software AGMarkLogic Corp.Apache Software Foundation
Initial release2013200920012006
Current release3.10.0, March 202211.0, December 20229.6.1, May 2024
License infoCommercial or Open SourcecommercialOpen Source infoApache Version 2; commercial licenses availablecommercial inforestricted free version is availableOpen Source infoApache Version 2
Cloud-based only infoOnly available as a cloud serviceyesnonono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageJavaC++Java
Server operating systemshostedAll OS with a Java VMLinux
OS X
Windows
All OS with a Java VM inforuns as a servlet in servlet container (e.g. Tomcat, Jetty is included)
Data schemeFlexible Schema (defined schema, partial schema, schema free)schema-freeschema-free infoSchema can be enforcedyes infoDynamic Fields enables on-the-fly addition of new fields
Typing infopredefined data types such as float or dateyesyesyes infosupports customizable data types and automatic typing
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.yesnoyesyes
Secondary indexesyesnoyesyes infoAll search fields are automatically indexed
SQL infoSupport of SQLwith Databricks SQLnoyes infoSQL92Solr Parallel SQL Interface
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
Java API
RESTful HTTP/JSON API
Supported programming languagesPython
R
Scala
JavaC
C#
C++
Java
JavaScript (Node.js)
Perl
PHP
Python
Ruby
.Net
Erlang
Java
JavaScript
any language that supports sockets and either XML or JSON
Perl
PHP
Python
Ruby
Scala
Server-side scripts infoStored proceduresuser defined functions and aggregatesnoyes infovia XQuery or JavaScriptJava plugins
Triggersyes infoCache Event Listenersyesyes infoUser configurable commands triggered on index changes
Partitioning methods infoMethods for storing different data on different nodesSharding infoby using Terracotta ServerShardingSharding
Replication methods infoMethods for redundantly storing data on multiple nodesyesyes infoby using Terracotta Serveryesyes
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyes infovia Hadoop Connector, HDFS Direct Access and in-database MapReduce jobsspark-solr: github.com/­lucidworks/­spark-solr and streaming expressions to reduce
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyTunable Consistency (Strong, Eventual, Weak)Immediate ConsistencyEventual Consistency
Foreign keys infoReferential integritynonono
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 transactionoptimistic locking
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyes infousing a tiered cache-storage approachyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyesyes, with Range Indexesyes
User concepts infoAccess controlnoRole-based access control at the document and subdocument levelsyes
More information provided by the system vendor
DatabricksEhcacheMarkLogicSolr
Specific characteristicsSupported database models : In addition to the Document store and Relational DBMS...
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DatabricksEhcacheMarkLogicSolr
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