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DBMS > Amazon Neptune vs. Blazegraph vs. Databricks vs. Drizzle vs. RDF4J

System Properties Comparison Amazon Neptune vs. Blazegraph vs. Databricks vs. Drizzle vs. RDF4J

Editorial information provided by DB-Engines
NameAmazon Neptune  Xexclude from comparisonBlazegraph  Xexclude from comparisonDatabricks  Xexclude from comparisonDrizzle  Xexclude from comparisonRDF4J infoformerly known as Sesame  Xexclude from comparison
Amazon has acquired Blazegraph's domain and (probably) product. It is said that Amazon Neptune is based on Blazegraph.Drizzle has published its last release in September 2012. The open-source project is discontinued and Drizzle is excluded from the DB-Engines ranking.
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.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.MySQL fork with a pluggable micro-kernel and with an emphasis of performance over compatibility.RDF4J is a Java framework for processing RDF data, supporting both memory-based and a disk-based storage.
Primary database modelGraph DBMS
RDF store
Graph DBMS
RDF store
Document store
Relational DBMS
Relational DBMSRDF store
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
Score81.08
Rank#15  Overall
#2  Document stores
#10  Relational DBMS
Score0.74
Rank#222  Overall
#9  RDF stores
Websiteaws.amazon.com/­neptuneblazegraph.comwww.databricks.comrdf4j.org
Technical documentationaws.amazon.com/­neptune/­developer-resourceswiki.blazegraph.comdocs.databricks.comrdf4j.org/­documentation
DeveloperAmazonBlazegraphDatabricksDrizzle project, originally started by Brian AkerSince 2016 officially forked into an Eclipse project, former developer was Aduna Software.
Initial release20172006201320082004
Current release2.1.5, March 20197.2.4, September 2012
License infoCommercial or Open SourcecommercialOpen Source infoextended commercial license availablecommercialOpen Source infoGNU GPLOpen 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 languageJavaC++Java
Server operating systemshostedLinux
OS X
Windows
hostedFreeBSD
Linux
OS X
Linux
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 dateyesyes infoRDF literal typesyesyes
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 languagewith Databricks SQLyes infowith proprietary extensionsno
APIs and other access methodsOpenCypher
RDF 1.1 / SPARQL 1.1
TinkerPop Gremlin
Java API
RESTful HTTP API
SPARQL QUERY
SPARQL UPDATE
TinkerPop 3
JDBC
ODBC
RESTful HTTP API
JDBCJava 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
.Net
C
C++
Java
JavaScript
PHP
Python
Ruby
Python
R
Scala
C
C++
Java
PHP
Java
PHP
Python
Server-side scripts infoStored proceduresnoyesuser defined functions and aggregatesnoyes
Triggersnonono infohooks for callbacks inside the server can be used.yes
Partitioning methods infoMethods for storing different data on different nodesnoneShardingShardingnone
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.yesyesMulti-source replication
Source-replica replication
none
MapReduce infoOffers an API for user-defined Map/Reduce methodsnononono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate Consistency or Eventual Consistency depending on configurationImmediate Consistency
Foreign keys infoReferential integrityyes infoRelationships in graphsyes infoRelationships in Graphsyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACIDACIDACIDACID 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.no
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)Pluggable authentication mechanisms infoe.g. LDAP, HTTPno
More information provided by the system vendor
Amazon NeptuneBlazegraphDatabricksDrizzleRDF4J infoformerly known as Sesame
Specific characteristicsSupported database models : In addition to the Document store and Relational DBMS...
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Amazon NeptuneBlazegraphDatabricksDrizzleRDF4J infoformerly known as Sesame
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