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DBMS > Badger vs. Databricks vs. EsgynDB vs. RDF4J

System Properties Comparison Badger vs. Databricks vs. EsgynDB vs. RDF4J

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Editorial information provided by DB-Engines
NameBadger  Xexclude from comparisonDatabricks  Xexclude from comparisonEsgynDB  Xexclude from comparisonRDF4J infoformerly known as Sesame  Xexclude from comparison
DescriptionAn embeddable, persistent, simple and fast Key-Value Store, written purely in Go.The 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 TrafodionRDF4J is a Java framework for processing RDF data, supporting both memory-based and a disk-based storage.
Primary database modelKey-value storeDocument store
Relational DBMS
Relational DBMSRDF store
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.22
Rank#320  Overall
#47  Key-value stores
Score81.08
Rank#15  Overall
#2  Document stores
#10  Relational DBMS
Score0.25
Rank#312  Overall
#138  Relational DBMS
Score0.74
Rank#222  Overall
#9  RDF stores
Websitegithub.com/­dgraph-io/­badgerwww.databricks.comwww.esgyn.cnrdf4j.org
Technical documentationgodoc.org/­github.com/­dgraph-io/­badgerdocs.databricks.comrdf4j.org/­documentation
DeveloperDGraph LabsDatabricksEsgynSince 2016 officially forked into an Eclipse project, former developer was Aduna Software.
Initial release2017201320152004
License infoCommercial or Open SourceOpen Source infoApache 2.0commercialcommercialOpen Source infoEclipse Distribution License (EDL), v1.0.
Cloud-based only infoOnly available as a cloud servicenoyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageGoC++, JavaJava
Server operating systemsBSD
Linux
OS X
Solaris
Windows
hostedLinuxLinux
OS X
Unix
Windows
Data schemeschema-freeFlexible Schema (defined schema, partial schema, schema free)yesyes infoRDF Schemas
Typing infopredefined data types such as float or datenoyesyes
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.noyesno
Secondary indexesnoyesyesyes
SQL infoSupport of SQLnowith Databricks SQLyesno
APIs and other access methodsJDBC
ODBC
RESTful HTTP API
ADO.NET
JDBC
ODBC
Java API
RIO infoRDF Input/Output
Sail API
SeRQL infoSesame RDF Query Language
Sesame REST HTTP Protocol
SPARQL
Supported programming languagesGoPython
R
Scala
All languages supporting JDBC/ODBC/ADO.NetJava
PHP
Python
Server-side scripts infoStored proceduresnouser defined functions and aggregatesJava Stored Proceduresyes
Triggersnonoyes
Partitioning methods infoMethods for storing different data on different nodesnoneShardingnone
Replication methods infoMethods for redundantly storing data on multiple nodesnoneyesMulti-source replication between multi datacentersnone
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyesno
Consistency concepts infoMethods to ensure consistency in a distributed systemnoneImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integritynoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACIDACIDACID infoIsolation support depends on the API used
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyesyesyes infoin-memory storage is supported as well
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.nonono
User concepts infoAccess controlnofine grained access rights according to SQL-standardno
More information provided by the system vendor
BadgerDatabricksEsgynDBRDF4J infoformerly known as Sesame
Specific characteristicsSupported database models : In addition to the Document store and Relational DBMS...
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BadgerDatabricksEsgynDBRDF4J infoformerly known as Sesame
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