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DBMS > Blazegraph vs. Databricks vs. InterSystems IRIS

System Properties Comparison Blazegraph vs. Databricks vs. InterSystems IRIS

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Editorial information provided by DB-Engines
NameBlazegraph  Xexclude from comparisonDatabricks  Xexclude from comparisonInterSystems IRIS  Xexclude from comparison
Amazon has acquired Blazegraph's domain and (probably) product. It is said that Amazon Neptune is based on Blazegraph.
DescriptionHigh-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.A containerised multi-model DBMS, interoperability and analytics data platform with wide capabilities for vertical and horizontal scalability
Primary database modelGraph DBMS
RDF store
Document store
Relational DBMS
Document store
Key-value store
Object oriented DBMS
Relational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.06
Rank#206  Overall
#18  Graph DBMS
#9  RDF stores
Score60.86
Rank#19  Overall
#3  Document stores
#13  Relational DBMS
Score3.06
Rank#105  Overall
#21  Document stores
#20  Key-value stores
#1  Object oriented DBMS
#52  Relational DBMS
Websiteblazegraph.comdatabricks.comwww.intersystems.com/­products/­intersystems-iris
Technical documentationwiki.blazegraph.comdatabricks.com/­documentationdocs.intersystems.com/­irislatest/­csp/­docbook/­DocBook.UI.Page.cls
DeveloperBlazegraphDatabricksInterSystems
Initial release200620132018
Current release2.1.5, March 20192021.1, June 2021
License infoCommercial or Open SourceOpen Source infoextended commercial license availableOpen Sourcecommercial
Cloud-based only infoOnly available as a cloud servicenoyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageJava
Server operating systemsLinux
OS X
Windows
hostedAIX
Linux
macOS
Windows
Data schemeschema-freeFlexible Schema (defined schema, partial schema, schema free)depending on used data model
Typing infopredefined data types such as float or dateyes infoRDF literal typesyes
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.yesyes
Secondary indexesyesyesyes
SQL infoSupport of SQLSPARQL is used as query languagewith Databricks SQLyes
APIs and other access methodsJava API
RESTful HTTP API
SPARQL QUERY
SPARQL UPDATE
TinkerPop 3
JDBC
ODBC
RESTful HTTP API
JDBC
ODBC
RESTful HTTP API
Supported programming languages.Net
C
C++
Java
JavaScript
PHP
Python
Ruby
Python
R
Scala
.Net
C++
Java
JavaScript (Node.js)
Python
Server-side scripts infoStored proceduresyesuser defined functions and aggregatesyes
Triggersnoyes
Partitioning methods infoMethods for storing different data on different nodesShardingSharding
Replication methods infoMethods for redundantly storing data on multiple nodesyesyesSource-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate Consistency or Eventual Consistency depending on configurationImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integrityyes infoRelationships in Graphsyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACIDACID
Concurrency infoSupport for concurrent manipulation of datayesyesyes
Durability infoSupport for making data persistentyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyes
User concepts infoAccess controlSecurity and Authentication via Web Application Container (Tomcat, Jetty)yes

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BlazegraphDatabricksInterSystems IRIS
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