DBMS > Dgraph vs. H2 vs. HEAVY.AI vs. HugeGraph vs. Lovefield

System Properties Comparison Dgraph vs. H2 vs. HEAVY.AI vs. HugeGraph vs. Lovefield

Editorial information provided by DB-Engines

Name

Description

Distributed and scalable native Graph DBMS

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

A high performance, column-oriented RDBMS, specifically developed to harness the massive parallelism of modern CPU and GPU hardware

A fast-speed and highly-scalable Graph DBMS

Embeddable relational database for web apps written in pure JavaScript

Primary database model

Secondary database models

Spatial DBMS

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

Score	1.48
Rank	#158	Overall
	#15	Graph DBMS

Score	8.22
Rank	#50	Overall
	#32	Relational DBMS

Score	2.10
Rank	#126	Overall
	#61	Relational DBMS

Score	0.15
Rank	#339	Overall
	#33	Graph DBMS

Score	0.32
Rank	#290	Overall
	#132	Relational DBMS

Website

dgraph.io

www.h2database.com

github.com/heavyai/heavydb
www.heavy.ai

github.com/hugegraph
hugegraph.apache.org

google.github.io/lovefield

Technical documentation

dgraph.io/docs

www.h2database.com/html/main.html

docs.heavy.ai

hugegraph.apache.org/docs

github.com/google/lovefield/blob/master/docs/spec_index.md

Developer

Dgraph Labs, Inc.

Thomas Mueller

HEAVY.AI, Inc.

Baidu

Google

Initial release

2016

2005

2016

2018

2014

Current release

2.2.220, July 2023

5.10, January 2022

0.9

2.1.12, February 2017

License

Commercial or Open Source

Open Source

Apache 2.0

Open Source

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

Open Source

Apache Version 2; enterprise edition available

Open Source

Apache Version 2.0

Open Source

Apache 2.0

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

C++ and CUDA

Java

JavaScript

Server operating systems

Linux
OS X
Windows

All OS with a Java VM

Linux

Linux
macOS
Unix

server-less, requires a JavaScript environment (browser, Node.js)

tested with Chrome, Firefox, IE, Safari

Data scheme

schema-free

yes

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

SQL

Support of SQL

yes

SQL-like query language

via JavaScript builder pattern

APIs and other access methods

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

JDBC
ODBC

JDBC
ODBC
Thrift
Vega

Java API
RESTful HTTP API
TinkerPop Gremlin

Supported programming languages

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

Java

All languages supporting JDBC/ODBC/Thrift
Python

Groovy
Java
Python

JavaScript

Server-side scripts

Stored procedures

Java Stored Procedures and User-Defined Functions

asynchronous Gremlin script jobs

Triggers

yes

Using read-only observers

Partitioning methods

Methods for storing different data on different nodes

yes

none

Sharding

Round robin

yes

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

none

Replication methods

Methods for redundantly storing data on multiple nodes

Synchronous replication via Raft

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

Multi-source replication

yes

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

none

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

Foreign keys

Referential integrity

yes

edges in graph

yes

Transaction concepts

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

ACID

Concurrency

Support for concurrent manipulation of data

yes

yes, multi-version concurrency control (MVCC)

yes

Durability

Support for making data persistent

yes

yes, by using IndexedDB or the cloud service Firebase Realtime Database

In-memory capabilities

Is there an option to define some or all structures to be held in-memory only.

yes

using MemoryDB

User concepts

Access control

Planned for future releases

fine grained access rights according to SQL-standard

Users, roles and permissions

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More resources

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