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DBMS > Google Cloud Datastore vs. GraphDB vs. Neo4j

System Properties Comparison Google Cloud Datastore vs. GraphDB vs. Neo4j

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Editorial information provided by DB-Engines
NameGoogle Cloud Datastore  Xexclude from comparisonGraphDB infoformer name: OWLIM  Xexclude from comparisonNeo4j  Xexclude from comparison
DescriptionAutomatically scaling NoSQL Database as a Service (DBaaS) on the Google Cloud PlatformEnterprise-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 modelDocument storeGraph DBMS
RDF store
Graph DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score3.70
Rank#71  Overall
#12  Document stores
Score2.57
Rank#95  Overall
#7  Graph DBMS
#3  RDF stores
Score47.59
Rank#20  Overall
#1  Graph DBMS
Websitecloud.google.com/­datastorewww.ontotext.comneo4j.com
Technical documentationcloud.google.com/­datastore/­docsgraphdb.ontotext.com/­documentationneo4j.com/­docs
DeveloperGoogleOntotextNeo4j, Inc.
Initial release200820002007
Current release10.4, October 20235.23, August 2024
License infoCommercial or Open Sourcecommercialcommercial infoSome plugins of GraphDB Workbench are open sourcedOpen Source infoGPL version3, commercial licenses available
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.
Implementation languageJavaJava, Scala
Server operating systemshostedAll 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 schemeschema-freeschema-free and OWL/RDFS-schema support; RDF shapesschema-free and schema-optional
Typing infopredefined data types such as float or dateyes, details hereyesyes
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 indexesyesyes, 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 query language (GQL)stored SPARQL accessed as SQL using Apache Calcite through JDBC/ODBCno
APIs and other access methodsgRPC (using protocol buffers) API
RESTful HTTP/JSON API
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 languages.Net
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
.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 proceduresusing Google App Enginewell-defined plugin interfaces; JavaScript server-side extensibilityyes infoUser defined Procedures and Functions
TriggersCallbacks using the Google Apps Enginenoyes infovia event handler
Partitioning methods infoMethods for storing different data on different nodesShardingnoneyes using Neo4j Fabric
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication using PaxosMulti-source replicationCausal Clustering using Raft protocol infoavailable in in Enterprise Version only
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes infousing Google Cloud Dataflownono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate Consistency or Eventual Consistency depending on type of query and configuration infoStrong Consistency is default for entity lookups and queries within an Entity Group (but can instead be made eventually consistent). Other queries are always eventual consistent.Immediate 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 integrityyes infovia ReferenceProperties or Ancestor pathsyes infoConstraint checkingyes infoRelationships in graphs
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACID infoSerializable Isolation within Transactions, Read Committed outside of TransactionsACIDACID
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 controlAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)Default 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
Google Cloud DatastoreGraphDB infoformer name: OWLIMNeo4j
News

Is a Knowledge Graph a Graph Database?
25 April 2025

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

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More resources
Google Cloud DatastoreGraphDB infoformer name: OWLIMNeo4j
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22 December 2015, Emil Eifrem (guest author)

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