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DBMS > Amazon Neptune vs. Blazegraph vs. RDF4J vs. searchxml vs. Splice Machine

System Properties Comparison Amazon Neptune vs. Blazegraph vs. RDF4J vs. searchxml vs. Splice Machine

Editorial information provided by DB-Engines
NameAmazon Neptune  Xexclude from comparisonBlazegraph  Xexclude from comparisonRDF4J infoformerly known as Sesame  Xexclude from comparisonsearchxml  Xexclude from comparisonSplice Machine  Xexclude from comparison
Amazon has acquired Blazegraph's domain and (probably) product. It is said that Amazon Neptune is based on Blazegraph.
DescriptionFast, reliable graph database built for the cloudHigh-performance graph database supporting Semantic Web (RDF/SPARQL) and Graph Database (tinkerpop3, blueprints, vertex-centric) APIs with scale-out and High Availability.RDF4J 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 serverOpen-Source SQL RDBMS for Operational and Analytical use cases with native Machine Learning, powered by Hadoop and Spark
Primary database modelGraph DBMS
RDF store
Graph DBMS
RDF store
RDF storeNative XML DBMS
Search engine
Relational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score2.29
Rank#113  Overall
#9  Graph DBMS
#5  RDF stores
Score0.81
Rank#213  Overall
#19  Graph DBMS
#8  RDF stores
Score0.74
Rank#222  Overall
#9  RDF stores
Score0.03
Rank#390  Overall
#7  Native XML DBMS
#24  Search engines
Score0.54
Rank#252  Overall
#115  Relational DBMS
Websiteaws.amazon.com/­neptuneblazegraph.comrdf4j.orgwww.searchxml.net/­category/­productssplicemachine.com
Technical documentationaws.amazon.com/­neptune/­developer-resourceswiki.blazegraph.comrdf4j.org/­documentationwww.searchxml.net/­support/­handoutssplicemachine.com/­how-it-works
DeveloperAmazonBlazegraphSince 2016 officially forked into an Eclipse project, former developer was Aduna Software.informationpartners gmbhSplice Machine
Initial release20172006200420152014
Current release2.1.5, March 20191.03.1, March 2021
License infoCommercial or Open SourcecommercialOpen Source infoextended commercial license availableOpen Source infoEclipse Distribution License (EDL), v1.0.commercialOpen Source infoAGPL 3.0, commercial license available
Cloud-based only infoOnly available as a cloud serviceyesnononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaJavaC++Java
Server operating systemshostedLinux
OS X
Windows
Linux
OS X
Unix
Windows
WindowsLinux
OS X
Solaris
Windows
Data schemeschema-freeschema-freeyes infoRDF Schemasschema-freeyes
Typing infopredefined data types such as float or dateyesyes infoRDF literal typesyesyesyes
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.noyes
Secondary indexesnoyesyesyesyes
SQL infoSupport of SQLnoSPARQL is used as query languagenonoyes
APIs and other access methodsOpenCypher
RDF 1.1 / SPARQL 1.1
TinkerPop Gremlin
Java API
RESTful HTTP API
SPARQL QUERY
SPARQL UPDATE
TinkerPop 3
Java API
RIO infoRDF Input/Output
Sail API
SeRQL infoSesame RDF Query Language
Sesame REST HTTP Protocol
SPARQL
RESTful HTTP API
WebDAV
XQuery
XSLT
JDBC
Native Spark Datasource
ODBC
Supported programming languagesC#
Go
Java
JavaScript
PHP
Python
Ruby
Scala
.Net
C
C++
Java
JavaScript
PHP
Python
Ruby
Java
PHP
Python
C++ infomost other programming languages supported via APIsC#
C++
Java
JavaScript (Node.js)
Python
R
Scala
Server-side scripts infoStored proceduresnoyesyesyes infoon the application serveryes infoJava
Triggersnonoyesnoyes
Partitioning methods infoMethods for storing different data on different nodesnoneShardingnonenoneShared Nothhing Auto-Sharding, Columnar Partitioning
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.yesnoneyes infosychronisation to multiple collectionsMulti-source replication
Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonononoYes, via Full Spark Integration
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate Consistency or Eventual Consistency depending on configurationImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integrityyes infoRelationships in graphsyes infoRelationships in Graphsnoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACIDACID infoIsolation support depends on the API usedmultiple readers, single writerACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes, multi-version concurrency control (MVCC)
Durability infoSupport for making data persistentyes infowith encyption-at-restyesyes infoin-memory storage is supported as wellyesyes
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)Security and Authentication via Web Application Container (Tomcat, Jetty)noDomain, group and role-based access control at the document level and for application servicesAccess rights for users, groups and roles according to SQL-standard

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More resources
Amazon NeptuneBlazegraphRDF4J infoformerly known as SesamesearchxmlSplice Machine
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