DBMS > HugeGraph vs. Neo4j vs. Sphinx vs. SQLite vs. Stardog

System Properties Comparison HugeGraph vs. Neo4j vs. Sphinx vs. SQLite vs. Stardog

Editorial information provided by DB-Engines

Name

Description

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

Open source search engine for searching in data from different sources, e.g. relational databases

Widely used embeddable, in-process RDBMS

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	0.13
Rank	#336	Overall
	#32	Graph DBMS

Score	44.46
Rank	#23	Overall
	#1	Graph DBMS

Score	5.98
Rank	#56	Overall
	#5	Search engines

Score	114.32
Rank	#10	Overall
	#7	Relational DBMS

Score	2.02
Rank	#123	Overall
	#11	Graph DBMS
	#6	RDF stores

Website

github.com/hugegraph
hugegraph.apache.org

Technical documentation

hugegraph.apache.org/docs

neo4j.com/docs

sphinxsearch.com/docs

www.sqlite.org/docs.html

docs.stardog.com

Developer

Baidu

Neo4j, Inc.

Sphinx Technologies Inc.

Dwayne Richard Hipp

Stardog-Union

Initial release

2018

2007

2001

2000

2010

Current release

0.9

5.19, April 2024

3.5.1, February 2023

3.45.3 (15 April 2024), April 2024

7.3.0, May 2020

License

Commercial or Open Source

Open Source

Apache Version 2.0

Open Source

GPL version3, commercial licenses available

Open Source

GPL version 2, commercial licence available

Open Source

Public Domain

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

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

C++

Java

Server operating systems

Linux
macOS
Unix

Linux

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

FreeBSD
Linux
NetBSD
OS X
Solaris
Windows

server-less

Linux
macOS
Windows

Data scheme

yes

schema-free and schema-optional

yes

dynamic column types

schema-free and OWL/RDFS-schema support

Typing

predefined data types such as float or date

yes

not rigid because of 'dynamic typing' concept.

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

also supports composite index and range index

yes

pluggable indexing subsystem, by default Apache Lucene

yes

full-text index on all search fields

yes

supports real-time indexing in full-text and geospatial

SQL

Support of SQL

SQL-like query language (SphinxQL)

yes

SQL-92 is not fully supported

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

APIs and other access methods

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

Proprietary protocol

ADO.NET

inofficial driver
JDBC

inofficial driver
ODBC

inofficial driver

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

Groovy
Java
Python

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

C++

unofficial client library
Java
Perl

unofficial client library
PHP
Python
Ruby

unofficial client library

Actionscript
Ada
Basic
C
C#
C++
D
Delphi
Forth
Fortran
Haskell
Java
JavaScript
Lisp
Lua
MatLab
Objective-C
OCaml
Perl
PHP
PL/SQL
Python
R
Ruby
Scala
Scheme
Smalltalk
Tcl

.Net
Clojure
Groovy
Java
JavaScript
Python
Ruby

Server-side scripts

Stored procedures

asynchronous Gremlin script jobs

yes

User defined Procedures and Functions

user defined functions and aggregates, HTTP Server extensions in Java

Triggers

yes

via event handler

yes

via event handlers

Partitioning methods

Methods for storing different data on different nodes

yes

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

yes using Neo4j Fabric

Sharding

Partitioning is done manually, search queries against distributed index is supported

none

Replication methods

Methods for redundantly storing data on multiple nodes

yes

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

Causal Clustering using Raft protocol

available in in Enterprise Version only

none

Multi-source replication in HA-Cluster

MapReduce

Offers an API for user-defined Map/Reduce methods

via hugegraph-spark

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency

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

edges in graph

yes

Relationships in graphs

yes

relationships in graphs

Transaction concepts

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

ACID

Concurrency

Support for concurrent manipulation of data

yes

via file-system locks

yes

Durability

Support for making data persistent

yes

The original contents of fields are not stored in the Sphinx index.

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

Users, roles and permissions

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

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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...
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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: Nodes 2024, Data Modelling, Events, Knowledge Graphs and more
27 April 2024

GQL is Here: Your Cypher Queries in a GQL World
26 April 2024

GQL: The ISO Standard for Graphs Has Arrived
25 April 2024

What Is Retrieval-Augmented Generation (RAG)?
24 April 2024

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

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