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DBMS > Apache Spark (SQL) vs. GraphDB vs. Neo4j

System Properties Comparison Apache Spark (SQL) vs. GraphDB vs. Neo4j

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Editorial information provided by DB-Engines
NameApache Spark (SQL)  Xexclude from comparisonGraphDB infoformer name: OWLIM  Xexclude from comparisonNeo4j  Xexclude from comparison
DescriptionApache Spark SQL is a component on top of 'Spark Core' for structured data processingEnterprise-ready RDF and graph database with efficient reasoning, cluster and external index synchronization support. It supports also SQL JDBC access to Knowledge Graph and GraphQL over SPARQL.Scalable, ACID-compliant graph database designed with a high-performance distributed cluster architecture, available in self-hosted and cloud offerings
Primary database modelRelational DBMSGraph DBMS
RDF store
Graph DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score20.40
Rank#29  Overall
#18  Relational DBMS
Score2.57
Rank#95  Overall
#7  Graph DBMS
#3  RDF stores
Score47.59
Rank#20  Overall
#1  Graph DBMS
Websitespark.apache.org/­sqlwww.ontotext.comneo4j.com
Technical documentationspark.apache.org/­docs/­latest/­sql-programming-guide.htmlgraphdb.ontotext.com/­documentationneo4j.com/­docs
DeveloperApache Software FoundationOntotextNeo4j, Inc.
Initial release201420002007
Current release3.5.0 ( 2.13), September 202310.4, October 20235.23, August 2024
License infoCommercial or Open SourceOpen Source infoApache 2.0commercial infoSome plugins of GraphDB Workbench are open sourcedOpen Source infoGPL version3, commercial licenses available
Cloud-based only infoOnly available as a cloud servicenonono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageScalaJavaJava, Scala
Server operating systemsLinux
OS X
Windows
All OS with a Java VM
Linux
OS X
Windows
Linux infoCan also be used server-less as embedded Java database.
OS X
Solaris
Windows
Data schemeyesschema-free and OWL/RDFS-schema support; RDF shapesschema-free and schema-optional
Typing infopredefined data types such as float or dateyesyesyes
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.nono
Secondary indexesnoyes, supports real-time synchronization and indexing in SOLR/Elastic search/Lucene and GeoSPARQL geometry data indexesyes infopluggable indexing subsystem, by default Apache Lucene
SQL infoSupport of SQLSQL-like DML and DDL statementsstored SPARQL accessed as SQL using Apache Calcite through JDBC/ODBCno
APIs and other access methodsJDBC
ODBC
GeoSPARQL
GraphQL
GraphQL Federation
Java API
JDBC
RDF4J API
RDFS
RIO
Sail API
Sesame REST HTTP Protocol
SPARQL 1.1
Bolt protocol
Cypher query language
Java API
Neo4j-OGM infoObject Graph Mapper
RESTful HTTP API
Spring Data Neo4j
TinkerPop 3
Supported programming languagesJava
Python
R
Scala
.Net
C#
Clojure
Java
JavaScript (Node.js)
PHP
Python
Ruby
Scala
.Net
Clojure
Elixir
Go
Groovy
Haskell
Java
JavaScript
Perl
PHP
Python
Ruby
Scala
Server-side scripts infoStored proceduresnowell-defined plugin interfaces; JavaScript server-side extensibilityyes infoUser defined Procedures and Functions
Triggersnonoyes infovia event handler
Partitioning methods infoMethods for storing different data on different nodesyes, utilizing Spark Corenoneyes using Neo4j Fabric
Replication methods infoMethods for redundantly storing data on multiple nodesnoneMulti-source replicationCausal Clustering using Raft protocol infoavailable in in Enterprise Version only
MapReduce infoOffers an API for user-defined Map/Reduce methodsnono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate Consistency, Eventual consistency (configurable in cluster mode per master or individual client request)Causal and Eventual Consistency configurable in Causal Cluster setup
Immediate Consistency in stand-alone mode
Foreign keys infoReferential integritynoyes infoConstraint checkingyes infoRelationships in graphs
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACIDACID
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.no
User concepts infoAccess controlnoDefault Basic authentication through RDF4J client, or via Java when run with cURL, default token-based in the Workbench or via Rest API, optional access through OpenID or Kerberos single sign-on.Users, roles and permissions. Pluggable authentication with supported standards (LDAP, Active Directory, Kerberos)
More information provided by the system vendor
Apache Spark (SQL)GraphDB infoformer name: OWLIMNeo4j
News

Transform Static Risk Assessment Into a Dynamic Data-Driven Strategy
22 April 2025

LLM Knowledge Graph Builder Back-End Architecture and API Overview
14 April 2025

Build an Intelligent Movie Search With Neo4j and Vertex AI
14 April 2025

This Week in Neo4j: NODES, GraphRAG, Agents, Knowledge Graph and more
12 April 2025

Google Cloud & Neo4j: Teaming Up at the Intersection of Knowledge Graphs, Agents, MCP, and Natural Language Interfaces
9 April 2025

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More resources
Apache Spark (SQL)GraphDB infoformer name: OWLIMNeo4j
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