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DBMS > Databricks vs. Neo4j vs. Stardog

System Properties Comparison Databricks vs. Neo4j vs. Stardog

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Editorial information provided by DB-Engines
NameDatabricks  Xexclude from comparisonNeo4j  Xexclude from comparisonStardog  Xexclude from comparison
DescriptionThe 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.Scalable, ACID-compliant graph database designed with a high-performance distributed cluster architecture, available in self-hosted and cloud offeringsEnterprise Knowledge Graph platform and graph DBMS with high availability, high performance reasoning, and virtualization
Primary database modelDocument store
Relational DBMS
Graph DBMSGraph DBMS
RDF store
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score86.46
Rank#14  Overall
#2  Document stores
#9  Relational DBMS
Score42.70
Rank#21  Overall
#1  Graph DBMS
Score1.78
Rank#130  Overall
#11  Graph DBMS
#6  RDF stores
Websitewww.databricks.comneo4j.comwww.stardog.com
Technical documentationdocs.databricks.comneo4j.com/­docsdocs.stardog.com
DeveloperDatabricksNeo4j, Inc.Stardog-Union
Initial release201320072010
Current release5.23, August 20247.3.0, May 2020
License infoCommercial or Open SourcecommercialOpen Source infoGPL version3, commercial licenses availablecommercial info60-day fully-featured trial license; 1-year fully-featured non-commercial use license for academics/students
Cloud-based only infoOnly available as a cloud serviceyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Neo4j Aura: Neo4j’s fully managed cloud service: The zero-admin, always-on graph database for cloud developers.
Implementation languageJava, ScalaJava
Server operating systemshostedLinux infoCan also be used server-less as embedded Java database.
OS X
Solaris
Windows
Linux
macOS
Windows
Data schemeFlexible Schema (defined schema, partial schema, schema free)schema-free and schema-optionalschema-free and OWL/RDFS-schema support
Typing infopredefined data types such as float or dateyesyes
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.yesno infoImport/export of XML data possible
Secondary indexesyesyes infopluggable indexing subsystem, by default Apache Luceneyes infosupports real-time indexing in full-text and geospatial
SQL infoSupport of SQLwith Databricks SQLnoYes, compatible with all major SQL variants through dedicated BI/SQL Server
APIs and other access methodsJDBC
ODBC
RESTful HTTP API
Bolt protocol
Cypher query language
Java API
Neo4j-OGM infoObject Graph Mapper
RESTful HTTP API
Spring Data Neo4j
TinkerPop 3
GraphQL query language
HTTP API
Jena RDF API
OWL
RDF4J API
Sesame REST HTTP Protocol
SNARL
SPARQL
Spring Data
Stardog Studio
TinkerPop 3
Supported programming languagesPython
R
Scala
.Net
Clojure
Elixir
Go
Groovy
Haskell
Java
JavaScript
Perl
PHP
Python
Ruby
Scala
.Net
Clojure
Groovy
Java
JavaScript
Python
Ruby
Server-side scripts infoStored proceduresuser defined functions and aggregatesyes infoUser defined Procedures and Functionsuser defined functions and aggregates, HTTP Server extensions in Java
Triggersyes infovia event handleryes infovia event handlers
Partitioning methods infoMethods for storing different data on different nodesyes using Neo4j Fabricnone
Replication methods infoMethods for redundantly storing data on multiple nodesyesCausal Clustering using Raft protocol infoavailable in in Enterprise Version onlyMulti-source replication in HA-Cluster
MapReduce infoOffers an API for user-defined Map/Reduce methodsnono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyCausal and Eventual Consistency configurable in Causal Cluster setup
Immediate Consistency in stand-alone mode
Immediate Consistency in HA-Cluster
Foreign keys infoReferential integrityyes infoRelationships in graphsyes inforelationships in graphs
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 controlUsers, roles and permissions. Pluggable authentication with supported standards (LDAP, Active Directory, Kerberos)Access rights for users and roles
More information provided by the system vendor
DatabricksNeo4jStardog
Specific characteristicsSupported database models : In addition to the Document store and Relational DBMS...
» more
Neo4j delivers graph technology that has been battle tested for performance and scale...
» more
Competitive advantagesNeo4j is the market leader, graph database category creator, and the most widely...
» more
Typical application scenariosReal-Time Recommendations Master Data Management Identity and Access Management Network...
» more
Key customersOver 800 commercial customers and over 4300 startups use Neo4j. Flagship customers...
» more
Market metricsNeo4j boasts the world's largest graph database ecosystem with more than 140 million...
» more
Licensing and pricing modelsGPL v3 license that can be used all the places where you might use MySQL. Neo4j Commercial...
» more
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