DBMS > Google BigQuery vs. Google Cloud Datastore vs. Neo4j vs. Stardog

System Properties Comparison Google BigQuery vs. Google Cloud Datastore vs. Neo4j vs. Stardog

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Editorial information provided by DB-Engines

Name

Description

Large scale data warehouse service with append-only tables

Automatically scaling NoSQL Database as a Service (DBaaS) on the Google Cloud Platform

Scalable, ACID-compliant graph database designed with a high-performance distributed cluster architecture, available in self-hosted and cloud offerings

Enterprise Knowledge Graph platform and graph DBMS with high availability, high performance reasoning, and virtualization

Primary database model

DB-Engines Ranking measures the popularity of database management systems
Trend Chart

Score	61.90
Rank	#19	Overall
	#13	Relational DBMS

Score	4.49
Rank	#79	Overall
	#12	Document stores

Score	44.47
Rank	#23	Overall
	#1	Graph DBMS

Score	2.05
Rank	#129	Overall
	#11	Graph DBMS
	#6	RDF stores

Website

cloud.google.com/bigquery

cloud.google.com/datastore

neo4j.com

www.stardog.com

Technical documentation

cloud.google.com/bigquery/docs

cloud.google.com/datastore/docs

neo4j.com/docs

docs.stardog.com

Developer

Google

Neo4j, Inc.

Stardog-Union

Initial release

2010

2008

2007

2010

Current release

5.19, April 2024

7.3.0, May 2020

License

Commercial or Open Source

commercial

Open Source

GPL version3, commercial licenses available

commercial

60-day fully-featured trial license; 1-year fully-featured non-commercial use license for academics/students

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database 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 language

Java, Scala

Java

Server operating systems

hosted

Linux

Can also be used server-less as embedded Java database.
OS X
Solaris
Windows

Linux
macOS
Windows

Data scheme

yes

schema-free

schema-free and schema-optional

schema-free and OWL/RDFS-schema support

Typing

predefined data types such as float or date

yes

yes, details here

yes

XML support

Some form of processing data in XML format, e.g. support for XML data structures, and/or support for XPath, XQuery or XSLT.

Import/export of XML data possible

Secondary indexes

yes

pluggable indexing subsystem, by default Apache Lucene

yes

supports real-time indexing in full-text and geospatial

SQL

Support of SQL

yes

SQL-like query language (GQL)

Yes, compatible with all major SQL variants through dedicated BI/SQL Server

APIs and other access methods

RESTful HTTP/JSON API

gRPC (using protocol buffers) API
RESTful HTTP/JSON API

Bolt protocol
Cypher query language
Java API
Neo4j-OGM

Object 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 languages

.Net
Java
JavaScript
Objective-C
PHP
Python
Ruby

.Net
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby

.Net
Clojure
Elixir
Go
Groovy
Haskell
Java
JavaScript
Perl
PHP
Python
Ruby
Scala

.Net
Clojure
Groovy
Java
JavaScript
Python
Ruby

Server-side scripts

Stored procedures

user defined functions

in JavaScript

using Google App Engine

yes

User defined Procedures and Functions

user defined functions and aggregates, HTTP Server extensions in Java

Triggers

Callbacks using the Google Apps Engine

yes

via event handler

yes

via event handlers

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

yes using Neo4j Fabric

none

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication using Paxos

Causal Clustering using Raft protocol

available in in Enterprise Version only

Multi-source replication in HA-Cluster

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

using Google Cloud Dataflow

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Immediate Consistency or Eventual Consistency depending on type of query and configuration

Strong 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.

Causal and Eventual Consistency configurable in Causal Cluster setup
Immediate Consistency in stand-alone mode

Immediate Consistency in HA-Cluster

Foreign keys

Referential integrity

yes

via ReferenceProperties or Ancestor paths

yes

Relationships in graphs

yes

relationships in graphs

Transaction concepts

Support to ensure data integrity after non-atomic manipulations of data

Since BigQuery is designed for querying data

ACID

Serializable Isolation within Transactions, Read Committed outside of Transactions

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

In-memory capabilities

Is there an option to define some or all structures to be held in-memory only.

yes

User concepts

Access control

Access privileges (owner, writer, reader) on dataset, table or view level

Google Cloud Identity & Access Management (IAM)

Access rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)

Users, 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

Specific characteristics

Neo4j delivers graph technology that has been battle tested for performance and scale...
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Competitive advantages

Neo4j is the market leader, graph database category creator, and the most widely...
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Typical application scenarios

Real-Time Recommendations Master Data Management Identity and Access Management Network...
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Key customers

Over 800 commercial customers and over 4300 startups use Neo4j. Flagship customers...
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Market metrics

Neo4j boasts the world's largest graph database ecosystem with more than 140 million...
» more

Licensing and pricing models

GPL v3 license that can be used all the places where you might use MySQL. Neo4j Commercial...
» more

News

This Week in Neo4j: Google Cloud, Analysis, Knowledge Graph, Relationships and more
20 April 2024

Announcing NODES 2024: Submit Your Talk
17 April 2024

ISO GQL: A Defining Moment in the History of Database Innovation
17 April 2024

This Week in Neo4j: Podcast, RAG, Neo4j Guide, ERP and more
13 April 2024

Neo4j Brings GraphRAG Capabilities for GenAI to Google Cloud
9 April 2024

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and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.