DBMS > Dgraph vs. HugeGraph vs. HyperSQL vs. Oracle NoSQL

System Properties Comparison Dgraph vs. HugeGraph vs. HyperSQL vs. Oracle NoSQL

Please select another system to include it in the comparison.

Editorial information provided by DB-Engines

Name

Description

Distributed and scalable native Graph DBMS

A fast-speed and highly-scalable Graph DBMS

Multithreaded, transactional RDBMS written in Java

also known as HSQLDB

A multi-model, scalable, distributed NoSQL database, designed to provide highly reliable, flexible, and available data management across a configurable set of storage nodes

Primary database model

Graph DBMS

Relational DBMS

Document store
Key-value store
Relational DBMS

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

Score	1.45
Rank	#156	Overall
	#15	Graph DBMS

Score	0.13
Rank	#336	Overall
	#32	Graph DBMS

Score	3.49
Rank	#87	Overall
	#47	Relational DBMS

Score	2.95
Rank	#100	Overall
	#17	Document stores
	#17	Key-value stores
	#50	Relational DBMS

Website

dgraph.io

github.com/hugegraph
hugegraph.apache.org

hsqldb.org

www.oracle.com/database/nosql/technologies/nosql

Technical documentation

dgraph.io/docs

hugegraph.apache.org/docs

hsqldb.org/web/hsqlDocsFrame.html

docs.oracle.com/en/database/other-databases/nosql-database/index.html

Developer

Dgraph Labs, Inc.

Baidu

Oracle

Initial release

2016

2018

2001

2011

Current release

0.9

2.7.2, June 2023

23.3, December 2023

License

Commercial or Open Source

Open Source

Apache 2.0

Open Source

Apache Version 2.0

Open Source

based on BSD license

Open Source

Proprietary for Enterprise Edition (Oracle Database EE license has Oracle NoSQL database EE covered: details)

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.

Implementation language

Java

Server operating systems

Linux
OS X
Windows

Linux
macOS
Unix

All OS with a Java VM

Embedded (into Java applications) and Client-Server operating modes

Linux
Solaris SPARC/x86

Data scheme

schema-free

yes

Support Fixed schema and Schema-less deployment with the ability to interoperate between them.

Typing

predefined data types such as float or date

yes

optional

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

also supports composite index and range index

yes

SQL

Support of SQL

yes

SQL-like DML and DDL statements

APIs and other access methods

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

Java API
RESTful HTTP API
TinkerPop Gremlin

HTTP API

JDBC via HTTP
JDBC
ODBC

RESTful HTTP API

Supported programming languages

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

Groovy
Java
Python

All languages supporting JDBC/ODBC
Java

C
C#
Go
Java
JavaScript (Node.js)
Python

Server-side scripts

Stored procedures

asynchronous Gremlin script jobs

Java, SQL

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

yes

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

none

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

Synchronous replication via Raft

yes

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

none

Electable source-replica replication per shard. Support distributed global deployment with Multi-region table feature

MapReduce

Offers an API for user-defined Map/Reduce methods

via hugegraph-spark

with Hadoop integration

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency

Immediate Consistency

Eventual Consistency
Immediate Consistency

depending on configuration

Foreign keys

Referential integrity

yes

edges in graph

yes

Transaction concepts

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

ACID

configurable

ACID within a storage node (=shard)

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

off heap cache

User concepts

Access control

Planned for future releases

Users, roles and permissions

fine grained access rights according to SQL-standard

Access rights for users and roles

More information provided by the system vendor

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.

Related products and services

We invite representatives of vendors of related products to contact us for presenting information about their offerings here.

More resources

Recent citations in the news

Dgraph on AWS: Setting up a horizontally scalable graph database | Amazon Web Services
1 September 2020, AWS Blog

Dgraph launches Slash GraphQL, a GraphQL-native database Backend-as-a-Service
10 September 2020, TechCrunch

Dgraph Rises to the Top Graph Database on GitHub With 11 G2 Badges and 11M Downloads
26 May 2021, Business Wire

Dgraph Raises $6M in Seed Funding
20 July 2022, FinSMEs

provided by Google News

Critical Apache HugeGraph Flaw Let Attackers Execute Remote Code
23 April 2024, GBHackers

provided by Google News

HyperSQL DataBase flaw leaves library vulnerable to RCE
24 October 2022, The Daily Swig

Introduction to JDBC with HSQLDB tutorial
14 November 2022, TheServerSide.com

provided by Google News

Enhance enterprise data security and trust: Must see Blockchain Technology sessions at Oracle CloudWorld 2023
21 August 2023, blogs.oracle.com

We built a geo-distributed, serverless modern app using the Oracle NoSQL Database Cloud Service
18 November 2021, blogs.oracle.com

Oracle Defends Relational DBs Against NoSQL Competitors
25 November 2015, eWeek

Larry Ellison Just Embraced the Enemy. Or Did He?
1 October 2012, WIRED

What You Need to Know About NoSQL Databases
17 February 2012, Forbes

provided by Google News

Share this page