DBMS > DataFS vs. Dgraph vs. Hawkular Metrics vs. HugeGraph vs. Lovefield

System Properties Comparison DataFS vs. Dgraph vs. Hawkular Metrics vs. HugeGraph vs. Lovefield

Editorial information provided by DB-Engines

Name

Description

All data is stored inside objects which are linked by so-called link attributes. Objects consist of classes which can be extended and de-extended at runtime. Graphs can be defined with a struct.

Distributed and scalable native Graph DBMS

Hawkular metrics is the metric storage of the Red Hat sponsored Hawkular monitoring system. It is based on Cassandra.

A fast-speed and highly-scalable Graph DBMS

Embeddable relational database for web apps written in pure JavaScript

Primary database model

Secondary database models

Graph DBMS

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

Score	0.06
Rank	#354	Overall
	#15	Object oriented DBMS

Score	1.45
Rank	#156	Overall
	#15	Graph DBMS

Score	0.00
Rank	#379	Overall
	#40	Time Series DBMS

Score	0.13
Rank	#336	Overall
	#32	Graph DBMS

Score	0.29
Rank	#293	Overall
	#133	Relational DBMS

Website

newdatabase.com

dgraph.io

www.hawkular.org

github.com/hugegraph
hugegraph.apache.org

google.github.io/lovefield

Technical documentation

dev.mobiland.com/Overview.xsp

dgraph.io/docs

www.hawkular.org/hawkular-metrics/docs/user-guide

hugegraph.apache.org/docs

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

Developer

Mobiland AG

Dgraph Labs, Inc.

Community supported by Red Hat

Baidu

Google

Initial release

2018

2016

2014

2018

2014

Current release

1.1.263, October 2022

0.9

2.1.12, February 2017

License

Commercial or Open Source

commercial

Open Source

Apache 2.0

Open Source

Apache 2.0

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

JavaScript

Server operating systems

Windows

Linux
OS X
Windows

Linux
macOS
Unix

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

tested with Chrome, Firefox, IE, Safari

Data scheme

Classes, Structs, and Lists are written in proprietary DataTypeDefinitionLanguage (.dtdl) and Objects consisting of those are written in proprietary DataAccessDefinitionLanguage (.dadl)

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

SQL-like query language

via JavaScript builder pattern

APIs and other access methods

.NET Client API
Proprietary client DLL
WinRT client

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

HTTP REST

Java API
RESTful HTTP API
TinkerPop Gremlin

Supported programming languages

.Net
C
C#
C++
VB.Net

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

Go
Java
Python
Ruby

Groovy
Java
Python

JavaScript

Server-side scripts

Stored procedures

asynchronous Gremlin script jobs

Triggers

no, except callback-events from server when changes happened

yes

via Hawkular Alerting

Using read-only observers

Partitioning methods

Methods for storing different data on different nodes

Proprietary Sharding system

yes

Sharding

based on Cassandra

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

selectable replication factor

based on Cassandra

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

based on Cassandra
Immediate Consistency

based on Cassandra

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

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

Windows-Profile

Planned for future releases

Users, roles and permissions

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