DBMS > Dgraph vs. Google BigQuery vs. JanusGraph vs. Neo4j

System Properties Comparison Dgraph vs. Google BigQuery vs. JanusGraph vs. Neo4j

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Editorial information provided by DB-Engines

Name

Description

Distributed and scalable native Graph DBMS

Large scale data warehouse service with append-only tables

A Graph DBMS optimized for distributed clusters

It was forked from the latest code base of Titan in January 2017

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

Primary database model

Graph DBMS

Relational DBMS

Graph DBMS

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

Score	1.45
Rank	#156	Overall
	#15	Graph DBMS

Score	60.38
Rank	#19	Overall
	#13	Relational DBMS

Score	1.94
Rank	#129	Overall
	#12	Graph DBMS

Score	44.46
Rank	#23	Overall
	#1	Graph DBMS

Website

dgraph.io

cloud.google.com/bigquery

janusgraph.org

neo4j.com

Technical documentation

dgraph.io/docs

cloud.google.com/bigquery/docs

docs.janusgraph.org

neo4j.com/docs

Developer

Dgraph Labs, Inc.

Google

Linux Foundation; originally developed as Titan by Aurelius

Neo4j, Inc.

Initial release

2016

2010

2017

2007

Current release

0.6.3, February 2023

5.20, May 2024

License

Commercial or Open Source

Open Source

Apache 2.0

commercial

Open Source

Apache 2.0

Open Source

GPL version3, commercial licenses available

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

Java, Scala

Server operating systems

Linux
OS X
Windows

hosted

Linux
OS X
Unix
Windows

Linux

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

Data scheme

schema-free

yes

schema-free and schema-optional

Typing

predefined data types such as float or date

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.

Secondary indexes

yes

pluggable indexing subsystem, by default Apache Lucene

SQL

Support of SQL

yes

APIs and other access methods

GraphQL query language
gRPC (using protocol buffers) API
HTTP API

RESTful HTTP/JSON API

Java API
TinkerPop Blueprints
TinkerPop Frames
TinkerPop Gremlin
TinkerPop Rexster

Bolt protocol
Cypher query language
Java API
Neo4j-OGM

Object Graph Mapper
RESTful HTTP API
Spring Data Neo4j
TinkerPop 3

Supported programming languages

C#
C++
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby

.Net
Java
JavaScript
Objective-C
PHP
Python
Ruby

Clojure
Java
Python

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

Server-side scripts

Stored procedures

user defined functions

in JavaScript

yes

User defined Procedures and Functions

Triggers

yes

via event handler

Partitioning methods

Methods for storing different data on different nodes

yes

none

yes

depending on the used storage backend (e.g. Cassandra, HBase, BerkeleyDB)

yes using Neo4j Fabric

Replication methods

Methods for redundantly storing data on multiple nodes

Synchronous replication via Raft

yes

Causal Clustering using Raft protocol

available in in Enterprise Version only

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

via Faunus, a graph analytics engine

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency
Immediate Consistency

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

Foreign keys

Referential integrity

yes

Relationships in graphs

yes

Relationships in graphs

Transaction concepts

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

ACID

Since BigQuery is designed for querying data

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

Supports various storage backends: Cassandra, HBase, Berkeley DB, Akiban, Hazelcast

yes

In-memory capabilities

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

User concepts

Access control

Planned for future releases

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

Google Cloud Identity & Access Management (IAM)

User authentification and security via Rexster Graph Server

Users, roles and permissions. Pluggable authentication with supported standards (LDAP, Active Directory, Kerberos)

More information provided by the system vendor

Specific characteristics

Neo4j delivers graph technology that has been battle tested for performance and scale...
» more

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

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