DBMS > Apache Doris vs. HugeGraph vs. Neo4j vs. Snowflake

System Properties Comparison Apache Doris vs. HugeGraph vs. Neo4j vs. Snowflake

Please select another system to include it in the comparison.

Editorial information provided by DB-Engines

Name

Description

An MPP-based analytics DBMS embracing the MySQL protocol

A fast-speed and highly-scalable Graph DBMS

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

Cloud-based data warehousing service for structured and semi-structured data

Primary database model

Relational DBMS

Graph DBMS

Relational DBMS

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

Score	0.57
Rank	#244	Overall
	#113	Relational DBMS

Score	0.13
Rank	#336	Overall
	#32	Graph DBMS

Score	44.46
Rank	#23	Overall
	#1	Graph DBMS

Score	121.33
Rank	#9	Overall
	#6	Relational DBMS

Website

doris.apache.org
github.com/apache/doris

github.com/hugegraph
hugegraph.apache.org

neo4j.com

www.snowflake.com

Technical documentation

github.com/apache/doris/wiki

hugegraph.apache.org/docs

neo4j.com/docs

docs.snowflake.net/manuals/index.html

Developer

Apache Software Foundation, originally contributed from Baidu

Baidu

Neo4j, Inc.

Snowflake Computing Inc.

Initial release

2017

2018

2007

2014

Current release

1.2.2, February 2023

0.9

5.19, April 2024

License

Commercial or Open Source

Open Source

Apache Version 2.0

Open Source

Apache Version 2.0

Open Source

GPL version3, commercial licenses available

commercial

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

Linux
macOS
Unix

Linux

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

hosted

Data scheme

yes

schema-free and schema-optional

yes

support of semi-structured data formats (JSON, XML, Avro)

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.

yes

Secondary indexes

yes

also supports composite index and range index

yes

pluggable indexing subsystem, by default Apache Lucene

SQL

Support of SQL

yes

APIs and other access methods

JDBC
MySQL client

Java API
RESTful HTTP API
TinkerPop Gremlin

Bolt protocol
Cypher query language
Java API
Neo4j-OGM

Object Graph Mapper
RESTful HTTP API
Spring Data Neo4j
TinkerPop 3

CLI Client
JDBC
ODBC

Supported programming languages

Java

Groovy
Java
Python

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

JavaScript (Node.js)
Python

Server-side scripts

Stored procedures

user defined functions

asynchronous Gremlin script jobs

yes

User defined Procedures and Functions

user defined functions

Triggers

yes

via event handler

similar concept for controling cloud resources

Partitioning methods

Methods for storing different data on different nodes

horizontal partitioning

yes

depending on used storage backend, e.g. Cassandra and HBase

yes using Neo4j Fabric

yes

Replication methods

Methods for redundantly storing data on multiple nodes

none

yes

depending on used storage backend, e.g. Cassandra and HBase

Causal Clustering using Raft protocol

available in in Enterprise Version only

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

via hugegraph-spark

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency

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

Immediate Consistency

Foreign keys

Referential integrity

yes

edges in graph

yes

Relationships in graphs

yes

Transaction concepts

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

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

fine grained access rights according to SQL-standard

Users, roles and permissions

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

Users with fine-grained authorization concept, user roles and pluggable authentication

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...
» more

Typical application scenarios

Real-Time Recommendations Master Data Management Identity and Access Management Network...
» more

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

Neo4j Joins the Connect with Confluent Partner Program
16 May 2024

10 Inspiring Projects to Spark Your NODES 2024 Presentation
15 May 2024

New Security Feature in Neo4j Aura: Customer Managed Keys
15 May 2024

Safeguarding Elections: How Graph Technology Powers Groundbreaking Research on Political Ads
13 May 2024

This Week in Neo4j: GraphRAG, Testcontainers, Metadata Management, App Dev and more
11 May 2024

We invite representatives of system vendors to contact us for updating and extending the system information,
and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.