DBMS > Dgraph vs. HEAVY.AI vs. HugeGraph vs. OrigoDB vs. searchxml

System Properties Comparison Dgraph vs. HEAVY.AI vs. HugeGraph vs. OrigoDB vs. searchxml

Editorial information provided by DB-Engines

Name

Description

Distributed and scalable native Graph DBMS

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

A fully ACID in-memory object graph database

DBMS for structured and unstructured content wrapped with an application server

Primary database model

Graph DBMS

Relational DBMS

Graph DBMS

Document store
Object oriented DBMS

Native XML DBMS
Search engine

Secondary database models

Spatial DBMS

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

Score	1.45
Rank	#156	Overall
	#15	Graph DBMS

Score	1.77
Rank	#141	Overall
	#65	Relational DBMS

Score	0.13
Rank	#336	Overall
	#32	Graph DBMS

Score	0.00
Rank	#383	Overall
	#53	Document stores
	#20	Object oriented DBMS

Score	0.00
Rank	#383	Overall
	#7	Native XML DBMS
	#25	Search engines

Website

dgraph.io

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

github.com/hugegraph
hugegraph.apache.org

origodb.com

www.searchxml.net/category/products

Technical documentation

dgraph.io/docs

docs.heavy.ai

hugegraph.apache.org/docs

origodb.com/docs

www.searchxml.net/support/handouts

Developer

Dgraph Labs, Inc.

HEAVY.AI, Inc.

Baidu

Robert Friberg et al

informationpartners gmbh

Initial release

2016

2018

2009

under the name LiveDB

2015

Current release

5.10, January 2022

0.9

1.0

License

Commercial or Open Source

Open Source

Apache 2.0

Open Source

Apache Version 2; enterprise edition available

Open Source

Apache Version 2.0

Open Source

commercial

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

C++ and CUDA

Java

C++

Server operating systems

Linux
OS X
Windows

Linux

Linux
macOS
Unix

Linux
Windows

Windows

Data scheme

schema-free

yes

schema-free

Typing

predefined data types such as float or date

yes

User defined using .NET types and collections

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.

can be achieved using .NET

yes

Secondary indexes

yes

also supports composite index and range index

yes

SQL

Support of SQL

yes

APIs and other access methods

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

JDBC
ODBC
Thrift
Vega

Java API
RESTful HTTP API
TinkerPop Gremlin

.NET Client API
HTTP API
LINQ

RESTful HTTP API
WebDAV
XQuery
XSLT

Supported programming languages

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

All languages supporting JDBC/ODBC/Thrift
Python

Groovy
Java
Python

.Net

C++

most other programming languages supported via APIs

Server-side scripts

Stored procedures

asynchronous Gremlin script jobs

yes

on the application server

Triggers

yes

Domain Events

Partitioning methods

Methods for storing different data on different nodes

yes

Sharding

Round robin

yes

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

horizontal partitioning

client side managed; servers are not synchronized

none

Replication methods

Methods for redundantly storing data on multiple nodes

Synchronous replication via Raft

Multi-source replication

yes

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

Source-replica replication

yes

sychronisation to multiple collections

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

Immediate Consistency

Foreign keys

Referential integrity

yes

edges in graph

depending on model

Transaction concepts

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

ACID

multiple readers, single writer

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

Write ahead log

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

Planned for future releases

fine grained access rights according to SQL-standard

Users, roles and permissions

Role based authorization

Domain, group and role-based access control at the document level and for application services

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More resources

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