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DBMS > Amazon Neptune vs. Databricks vs. RDF4J vs. SQLite

System Properties Comparison Amazon Neptune vs. Databricks vs. RDF4J vs. SQLite

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Editorial information provided by DB-Engines
NameAmazon Neptune  Xexclude from comparisonDatabricks  Xexclude from comparisonRDF4J infoformerly known as Sesame  Xexclude from comparisonSQLite  Xexclude from comparison
DescriptionFast, reliable graph database built for the cloudThe 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.RDF4J is a Java framework for processing RDF data, supporting both memory-based and a disk-based storage.Widely used embeddable, in-process RDBMS
Primary database modelGraph DBMS
RDF store
Document store
Relational DBMS
RDF storeRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score2.20
Rank#113  Overall
#9  Graph DBMS
#5  RDF stores
Score84.24
Rank#14  Overall
#2  Document stores
#9  Relational DBMS
Score0.72
Rank#222  Overall
#9  RDF stores
Score103.35
Rank#10  Overall
#7  Relational DBMS
Websiteaws.amazon.com/­neptunewww.databricks.comrdf4j.orgwww.sqlite.org
Technical documentationaws.amazon.com/­neptune/­developer-resourcesdocs.databricks.comrdf4j.org/­documentationwww.sqlite.org/­docs.html
DeveloperAmazonDatabricksSince 2016 officially forked into an Eclipse project, former developer was Aduna Software.Dwayne Richard Hipp
Initial release2017201320042000
Current release3.46.1  (13 August 2024), August 2024
License infoCommercial or Open SourcecommercialcommercialOpen Source infoEclipse Distribution License (EDL), v1.0.Open Source infoPublic Domain
Cloud-based only infoOnly available as a cloud serviceyesyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaC
Server operating systemshostedhostedLinux
OS X
Unix
Windows
server-less
Data schemeschema-freeFlexible Schema (defined schema, partial schema, schema free)yes infoRDF Schemasyes infodynamic column types
Typing infopredefined data types such as float or dateyesyesyes infonot rigid because of 'dynamic typing' concept.
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 SQLnoyes infoSQL-92 is not fully supported
APIs and other access methodsOpenCypher
RDF 1.1 / SPARQL 1.1
TinkerPop Gremlin
JDBC
ODBC
RESTful HTTP API
Java API
RIO infoRDF Input/Output
Sail API
SeRQL infoSesame RDF Query Language
Sesame REST HTTP Protocol
SPARQL
ADO.NET infoinofficial driver
JDBC infoinofficial driver
ODBC infoinofficial driver
Supported programming languagesC#
Go
Java
JavaScript
PHP
Python
Ruby
Scala
Python
R
Scala
Java
PHP
Python
Actionscript
Ada
Basic
C
C#
C++
D
Delphi
Forth
Fortran
Haskell
Java
JavaScript
Lisp
Lua
MatLab
Objective-C
OCaml
Perl
PHP
PL/SQL
Python
R
Ruby
Scala
Scheme
Smalltalk
Tcl
Server-side scripts infoStored proceduresnouser defined functions and aggregatesyesno
Triggersnoyesyes
Partitioning methods infoMethods for storing different data on different nodesnonenonenone
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.yesnonenone
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integrityyes infoRelationships in graphsyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACIDACID infoIsolation support depends on the API usedACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes infovia file-system locks
Durability infoSupport for making data persistentyes infowith encyption-at-restyesyes 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.noyes
User concepts infoAccess controlAccess rights for users and roles can be defined via the AWS Identity and Access Management (IAM)nono
More information provided by the system vendor
Amazon NeptuneDatabricksRDF4J infoformerly known as SesameSQLite
Specific characteristicsSupported database models : In addition to the Document store and Relational DBMS...
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More resources
Amazon NeptuneDatabricksRDF4J infoformerly known as SesameSQLite
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