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DBMS > Databricks vs. MarkLogic vs. Solr vs. WakandaDB

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

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Editorial information provided by DB-Engines
NameDatabricks  Xexclude from comparisonMarkLogic  Xexclude from comparisonSolr  Xexclude from comparisonWakandaDB  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.Operational and transactional Enterprise NoSQL databaseA widely used distributed, scalable search engine based on Apache LuceneWakandaDB is embedded in a server that provides a REST API and a server-side javascript engine to access data
Primary database modelDocument store
Relational DBMS
Document store
Native XML DBMS
RDF store infoas of version 7
Search engine
Search engineObject oriented DBMS
Secondary database modelsSpatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score78.61
Rank#15  Overall
#2  Document stores
#10  Relational DBMS
Score5.92
Rank#58  Overall
#10  Document stores
#1  Native XML DBMS
#1  RDF stores
#6  Search engines
Score42.91
Rank#24  Overall
#3  Search engines
Score0.03
Rank#364  Overall
#17  Object oriented DBMS
Websitewww.databricks.comwww.marklogic.comsolr.apache.orgwakanda.github.io
Technical documentationdocs.databricks.comdocs.marklogic.comsolr.apache.org/­resources.htmlwakanda.github.io/­doc
DeveloperDatabricksMarkLogic Corp.Apache Software FoundationWakanda SAS
Initial release2013200120062012
Current release11.0, December 20229.6.0, April 20242.7.0 (April 29, 2019), April 2019
License infoCommercial or Open Sourcecommercialcommercial inforestricted free version is availableOpen Source infoApache Version 2Open Source infoAGPLv3, extended commercial license available
Cloud-based only infoOnly available as a cloud serviceyesnonono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC++JavaC++, JavaScript
Server operating systemshostedLinux
OS X
Windows
All OS with a Java VM inforuns as a servlet in servlet container (e.g. Tomcat, Jetty is included)Linux
OS X
Windows
Data schemeFlexible Schema (defined schema, partial schema, schema free)schema-free infoSchema can be enforcedyes infoDynamic Fields enables on-the-fly addition of new fieldsyes
Typing infopredefined data types such as float or dateyesyes infosupports customizable data types and automatic typingyes
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.yesyesyesno
Secondary indexesyesyesyes infoAll search fields are automatically indexed
SQL infoSupport of SQLwith Databricks SQLyes infoSQL92Solr Parallel SQL Interfaceno
APIs and other access methodsJDBC
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
Java API
RESTful HTTP/JSON API
RESTful HTTP API
Supported programming languagesPython
R
Scala
C
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
JavaScript
Server-side scripts infoStored proceduresuser defined functions and aggregatesyes infovia XQuery or JavaScriptJava pluginsyes
Triggersyesyes infoUser configurable commands triggered on index changesyes
Partitioning methods infoMethods for storing different data on different nodesShardingShardingnone
Replication methods infoMethods for redundantly storing data on multiple nodesyesyesyesnone
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes infovia Hadoop Connector, HDFS Direct Access and in-database MapReduce jobsspark-solr: github.com/­lucidworks/­spark-solr and streaming expressions to reduceno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyEventual ConsistencyImmediate Consistency
Foreign keys infoReferential integritynono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACID infocan act as a resource manager in an XA/JTA transactionoptimistic lockingACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyes, with Range Indexesyesno
User concepts infoAccess controlRole-based access control at the document and subdocument levelsyesyes
More information provided by the system vendor
DatabricksMarkLogicSolrWakandaDB
Specific characteristicsSupported database models : In addition to the Document store and Relational DBMS...
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DatabricksMarkLogicSolrWakandaDB
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