DBMS > H2 vs. HugeGraph vs. NebulaGraph vs. Riak KV

System Properties Comparison H2 vs. HugeGraph vs. NebulaGraph vs. Riak KV

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Editorial information provided by DB-Engines

Name

Description

Full-featured RDBMS with a small footprint, either embedded into a Java application or used as a database server.

A fast-speed and highly-scalable Graph DBMS

A distributed, linear scalable, high perfomant Graph DBMS

Distributed, fault tolerant key-value store

Primary database model

Relational DBMS

Graph DBMS

Key-value store

with links between data sets and object tags for the creation of secondary indexes

Secondary database models

Spatial DBMS

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

Score	8.13
Rank	#49	Overall
	#31	Relational DBMS

Score	0.13
Rank	#336	Overall
	#32	Graph DBMS

Score	2.14
Rank	#120	Overall
	#10	Graph DBMS

Score	4.10
Rank	#82	Overall
	#9	Key-value stores

Website

www.h2database.com

github.com/hugegraph
hugegraph.apache.org

github.com/vesoft-inc/nebula
www.nebula-graph.io

Technical documentation

www.h2database.com/html/main.html

hugegraph.apache.org/docs

docs.nebula-graph.io

www.tiot.jp/riak-docs/riak/kv/latest

Developer

Thomas Mueller

Baidu

Vesoft Inc.

OpenSource, formerly Basho Technologies

Initial release

2005

2018

2019

2009

Current release

2.2.220, July 2023

0.9

3.2.0, December 2022

License

Commercial or Open Source

Open Source

dual-licence (Mozilla public license, Eclipse public license)

Open Source

Apache Version 2.0

Open Source

Apache Version 2.0 + Common Clause 1.0

Open Source

Apache version 2, commercial enterprise edition

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

Java

C++

Erlang

Server operating systems

All OS with a Java VM

Linux
macOS
Unix

Linux

Linux
OS X

Data scheme

yes

Strong typed schema

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

also supports composite index and range index

yes

Nebula Graph internally uses the Key-Value store RocksDB for persistency. The vertices, edges, and their properties are stored as Key while their values are stored as Value. The primary indexes are per Key and secondary indexes are per Value.

restricted

SQL

Support of SQL

yes

SQL-like query language

APIs and other access methods

JDBC
ODBC

Java API
RESTful HTTP API
TinkerPop Gremlin

Browser interface
console (shell)
Cypher Query Language
GO Object Graph Mapper
Java Object Graph Mapper
NGBatis

ORM framework for NebulaGraph and Spring-Boot
Proprietary native API
Python Object Graph Mapper
Query language nGQL

HTTP API
Native Erlang Interface

Supported programming languages

Java

Groovy
Java
Python

.Net
C++
Go
Java
PHP
Python

unofficial client library
C#
C++

unofficial client library
Clojure

unofficial client library
Dart

unofficial client library
Erlang
Go

unofficial client library
Groovy

unofficial client library
Haskell

unofficial client library
Java
JavaScript

unofficial client library
Lisp

unofficial client library
Perl

unofficial client library
PHP
Python
Ruby
Scala

unofficial client library
Smalltalk

unofficial client library

Server-side scripts

Stored procedures

Java Stored Procedures and User-Defined Functions

asynchronous Gremlin script jobs

user defined functions

Erlang

Triggers

yes

pre-commit hooks and post-commit hooks

Partitioning methods

Methods for storing different data on different nodes

none

yes

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

Sharding

no "single point of failure"

Replication methods

Methods for redundantly storing data on multiple nodes

With clustering: 2 database servers on different computers operate on identical copies of a database

yes

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

Causal Clustering using Raft protocol

selectable replication factor

MapReduce

Offers an API for user-defined Map/Reduce methods

via hugegraph-spark

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency

Immediate Consistency

Eventual Consistency

Foreign keys

Referential integrity

yes

edges in graph

yes

Relationships in graphs

links between data sets can be stored

Transaction concepts

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

ACID

Concurrency

Support for concurrent manipulation of data

yes, multi-version concurrency control (MVCC)

yes

Durability

Support for making data persistent

yes

using RocksDB

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

Role-based access control

yes, using Riak Security

More information provided by the system vendor

Specific characteristics

NebulaGraph is a truly distributed, linearly scalable, lightning-fast graph database,...
» more

Competitive advantages

NebulaGraph boasts the world's only graph database solution that is able to host...
» more

Typical application scenarios

Social networking Fraud detection Knowledge graph Data warehouse management Anti...
» more

Key customers

Companies from a variety of industries have implemented NebulaGraph Database in production,...
» more

Market metrics

At our very early stage, NebulaGraph has already received over 10,000 stars on GitHub...
» more

Licensing and pricing models

NebulaGraph is open source and free to use under Apache 2.0 license.
» more

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

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