DBMS > Dolt vs. Google BigQuery vs. Neo4j vs. RavenDB

System Properties Comparison Dolt vs. Google BigQuery vs. Neo4j vs. RavenDB

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Editorial information provided by DB-Engines

Name

Description

A MySQL compatible DBMS with Git-like versioning of data and schema

Large scale data warehouse service with append-only tables

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

Open Source Operational and Transactional Enterprise NoSQL Document Database

Primary database model

Relational DBMS

Graph DBMS

Document store

Secondary database models

Document store

Graph DBMS
Spatial DBMS
Time Series DBMS

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

Score	1.02
Rank	#191	Overall
	#89	Relational DBMS

Score	58.10
Rank	#19	Overall
	#13	Relational DBMS

Score	44.89
Rank	#21	Overall
	#1	Graph DBMS

Score	2.84
Rank	#101	Overall
	#18	Document stores

Website

github.com/dolthub/dolt
www.dolthub.com

cloud.google.com/bigquery

neo4j.com

ravendb.net

Technical documentation

docs.dolthub.com

cloud.google.com/bigquery/docs

neo4j.com/docs

ravendb.net/docs

Developer

DoltHub Inc

Google

Neo4j, Inc.

Hibernating Rhinos

Initial release

2018

2010

2007

2010

Current release

5.20, May 2024

5.4, July 2022

License

Commercial or Open Source

Open Source

Apache Version 2.0

commercial

Open Source

GPL version3, commercial licenses available

Open Source

AGPL version 3, commercial license 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, Scala

Server operating systems

Linux
macOS
Windows

hosted

Linux

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

Linux
macOS
Raspberry Pi
Windows

Data scheme

yes

schema-free and schema-optional

schema-free

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

yes

SQL

Support of SQL

yes

SQL-like query language (RQL)

APIs and other access methods

CLI Client
HTTP REST

RESTful HTTP/JSON API

Bolt protocol
Cypher query language
Java API
Neo4j-OGM

Object Graph Mapper
RESTful HTTP API
Spring Data Neo4j
TinkerPop 3

.NET Client API
F# Client API
Go Client API
Java Client API
NodeJS Client API
PHP Client API
Python Client API
RESTful HTTP API

Supported programming languages

Ada
C
C#
C++
D
Delphi
Eiffel
Erlang
Haskell
Java
JavaScript (Node.js)
Objective-C
OCaml
Perl
PHP
Python
Ruby
Scheme
Tcl

.Net
Java
JavaScript
Objective-C
PHP
Python
Ruby

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

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

Server-side scripts

Stored procedures

yes

currently in alpha release

user defined functions

in JavaScript

yes

User defined Procedures and Functions

yes

Triggers

yes

via event handler

yes

Partitioning methods

Methods for storing different data on different nodes

none

yes using Neo4j Fabric

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

A database can be cloned to multiple locations and be used there in isolation. Data/schema changes can be pushed/pulled explicitly between locations.

Causal Clustering using Raft protocol

available in in Enterprise Version only

Multi-source replication

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

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

Default ACID transactions on the local node (eventually consistent across the cluster). Atomic operations with cluster-wide ACID transactions. Eventual consistency for indexes and full-text search indexes.

Foreign keys

Referential integrity

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

ACID, Cluster-wide transaction available

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.

User concepts

Access control

Only one user is configurable, and must be specified in the config file at startup

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

Google Cloud Identity & Access Management (IAM)

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

Authorization levels configured per client per database

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...
» more

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

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8 June 2024

Neo4j and Snowflake Bring Graph Data Science Into the AI Data Cloud
4 June 2024

RDF vs. Property Graphs: Choosing the Right Approach for Implementing a Knowledge Graph
4 June 2024

This Week in Neo4j: Importing Data, NODES, GenAI, Going Meta and more
1 June 2024

openCypher Will Pave the Road to GQL for Cypher Implementers
22 May 2024

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