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DBMS > Amazon Neptune vs. Badger vs. Databricks vs. Kinetica vs. RDF4J

System Properties Comparison Amazon Neptune vs. Badger vs. Databricks vs. Kinetica vs. RDF4J

Editorial information provided by DB-Engines
NameAmazon Neptune  Xexclude from comparisonBadger  Xexclude from comparisonDatabricks  Xexclude from comparisonKinetica  Xexclude from comparisonRDF4J infoformerly known as Sesame  Xexclude from comparison
DescriptionFast, reliable graph database built for the cloudAn 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.Fully vectorized database across both GPUs and CPUsRDF4J is a Java framework for processing RDF data, supporting both memory-based and a disk-based storage.
Primary database modelGraph DBMS
RDF store
Key-value storeDocument store
Relational DBMS
Relational DBMSRDF store
Secondary database modelsSpatial DBMS
Time Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score2.20
Rank#119  Overall
#9  Graph DBMS
#5  RDF stores
Score0.14
Rank#331  Overall
#49  Key-value stores
Score78.61
Rank#15  Overall
#2  Document stores
#10  Relational DBMS
Score0.64
Rank#236  Overall
#109  Relational DBMS
Score0.69
Rank#230  Overall
#9  RDF stores
Websiteaws.amazon.com/­neptunegithub.com/­dgraph-io/­badgerwww.databricks.comwww.kinetica.comrdf4j.org
Technical documentationaws.amazon.com/­neptune/­developer-resourcesgodoc.org/­github.com/­dgraph-io/­badgerdocs.databricks.comdocs.kinetica.comrdf4j.org/­documentation
DeveloperAmazonDGraph LabsDatabricksKineticaSince 2016 officially forked into an Eclipse project, former developer was Aduna Software.
Initial release20172017201320122004
Current release7.1, August 2021
License infoCommercial or Open SourcecommercialOpen Source infoApache 2.0commercialcommercialOpen Source infoEclipse Distribution License (EDL), v1.0.
Cloud-based only infoOnly available as a cloud serviceyesnoyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageGoC, C++Java
Server operating systemshostedBSD
Linux
OS X
Solaris
Windows
hostedLinuxLinux
OS X
Unix
Windows
Data schemeschema-freeschema-freeFlexible Schema (defined schema, partial schema, schema free)yesyes infoRDF Schemas
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.nonoyesno
Secondary indexesnonoyesyesyes
SQL infoSupport of SQLnonowith Databricks SQLSQL-like DML and DDL statementsno
APIs and other access methodsOpenCypher
RDF 1.1 / SPARQL 1.1
TinkerPop Gremlin
JDBC
ODBC
RESTful HTTP API
JDBC
ODBC
RESTful HTTP API
Java API
RIO infoRDF Input/Output
Sail API
SeRQL infoSesame RDF Query Language
Sesame REST HTTP Protocol
SPARQL
Supported programming languagesC#
Go
Java
JavaScript
PHP
Python
Ruby
Scala
GoPython
R
Scala
C++
Java
JavaScript (Node.js)
Python
Java
PHP
Python
Server-side scripts infoStored proceduresnonouser defined functions and aggregatesuser defined functionsyes
Triggersnonoyes infotriggers when inserted values for one or more columns fall within a specified rangeyes
Partitioning methods infoMethods for storing different data on different nodesnonenoneShardingnone
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-availability zones high availability, asynchronous replication for up to 15 read replicas within a single region. Global database clusters consists of a primary write DB cluster in one region, and up to five secondary read DB clusters in different regions. Each secondary region can have up to 16 reader instances.noneyesSource-replica replicationnone
MapReduce infoOffers an API for user-defined Map/Reduce methodsnononono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencynoneImmediate ConsistencyImmediate Consistency or Eventual Consistency depending on configuration
Foreign keys infoReferential integrityyes infoRelationships in graphsnoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDnoACIDnoACID infoIsolation support depends on the API used
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
Durability infoSupport for making data persistentyes infowith encyption-at-restyesyesyesyes 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.nonoyes infoGPU vRAM or System RAM
User concepts infoAccess controlAccess rights for users and roles can be defined via the AWS Identity and Access Management (IAM)noAccess rights for users and roles on table levelno
More information provided by the system vendor
Amazon NeptuneBadgerDatabricksKineticaRDF4J infoformerly known as Sesame
Specific characteristicsSupported database models : In addition to the Document store and Relational DBMS...
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More resources
Amazon NeptuneBadgerDatabricksKineticaRDF4J infoformerly known as Sesame
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