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DBMS > Databricks vs. EsgynDB vs. PouchDB vs. RDF4J vs. searchxml

System Properties Comparison Databricks vs. EsgynDB vs. PouchDB vs. RDF4J vs. searchxml

Editorial information provided by DB-Engines
NameDatabricks  Xexclude from comparisonEsgynDB  Xexclude from comparisonPouchDB  Xexclude from comparisonRDF4J infoformerly known as Sesame  Xexclude from comparisonsearchxml  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.Enterprise-class SQL-on-Hadoop solution, powered by Apache TrafodionJavaScript DBMS with an API inspired by CouchDBRDF4J is a Java framework for processing RDF data, supporting both memory-based and a disk-based storage.DBMS for structured and unstructured content wrapped with an application server
Primary database modelDocument store
Relational DBMS
Relational DBMSDocument storeRDF storeNative XML DBMS
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
Score0.16
Rank#329  Overall
#146  Relational DBMS
Score2.28
Rank#115  Overall
#21  Document stores
Score0.69
Rank#230  Overall
#9  RDF stores
Score0.00
Rank#383  Overall
#7  Native XML DBMS
#25  Search engines
Websitewww.databricks.comwww.esgyn.cnpouchdb.comrdf4j.orgwww.searchxml.net/­category/­products
Technical documentationdocs.databricks.compouchdb.com/­guidesrdf4j.org/­documentationwww.searchxml.net/­support/­handouts
DeveloperDatabricksEsgynApache Software FoundationSince 2016 officially forked into an Eclipse project, former developer was Aduna Software.informationpartners gmbh
Initial release20132015201220042015
Current release7.1.1, June 20191.0
License infoCommercial or Open SourcecommercialcommercialOpen SourceOpen Source infoEclipse Distribution License (EDL), v1.0.commercial
Cloud-based only infoOnly available as a cloud serviceyesnononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC++, JavaJavaScriptJavaC++
Server operating systemshostedLinuxserver-less, requires a JavaScript environment (browser, Node.js)Linux
OS X
Unix
Windows
Windows
Data schemeFlexible Schema (defined schema, partial schema, schema free)yesschema-freeyes infoRDF Schemasschema-free
Typing infopredefined data types such as float or dateyesnoyesyes
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.yesnonoyes
Secondary indexesyesyesyes infovia viewsyesyes
SQL infoSupport of SQLwith Databricks SQLyesnonono
APIs and other access methodsJDBC
ODBC
RESTful HTTP API
ADO.NET
JDBC
ODBC
HTTP REST infoonly for PouchDB Server
JavaScript API
Java API
RIO infoRDF Input/Output
Sail API
SeRQL infoSesame RDF Query Language
Sesame REST HTTP Protocol
SPARQL
RESTful HTTP API
WebDAV
XQuery
XSLT
Supported programming languagesPython
R
Scala
All languages supporting JDBC/ODBC/ADO.NetJavaScriptJava
PHP
Python
C++ infomost other programming languages supported via APIs
Server-side scripts infoStored proceduresuser defined functions and aggregatesJava Stored ProceduresView functions in JavaScriptyesyes infoon the application server
Triggersnoyesyesno
Partitioning methods infoMethods for storing different data on different nodesShardingSharding infowith a proxy-based framework, named couchdb-loungenonenone
Replication methods infoMethods for redundantly storing data on multiple nodesyesMulti-source replication between multi datacentersMulti-source replication infoalso with CouchDB databases
Source-replica replication infoalso with CouchDB databases
noneyes infosychronisation to multiple collections
MapReduce infoOffers an API for user-defined Map/Reduce methodsyesyesnono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyEventual ConsistencyImmediate Consistency
Foreign keys infoReferential integrityyesnono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACIDnoACID infoIsolation support depends on the API usedmultiple readers, single writer
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyesyes infoby using IndexedDB, WebSQL or LevelDB as backendyes infoin-memory storage is supported as wellyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.nonoyesno
User concepts infoAccess controlfine grained access rights according to SQL-standardnonoDomain, group and role-based access control at the document level and for application services
More information provided by the system vendor
DatabricksEsgynDBPouchDBRDF4J infoformerly known as Sesamesearchxml
Specific characteristicsSupported database models : In addition to the Document store and Relational DBMS...
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More resources
DatabricksEsgynDBPouchDBRDF4J infoformerly known as Sesamesearchxml
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