DBMS > Dgraph vs. GBase vs. HugeGraph vs. Lovefield vs. Teradata

System Properties Comparison Dgraph vs. GBase vs. HugeGraph vs. Lovefield vs. Teradata

Editorial information provided by DB-Engines

Name

Description

Distributed and scalable native Graph DBMS

Widely used RDBMS in China, including analytical, transactional, distributed transactional, and cloud-native data warehousing.

A fast-speed and highly-scalable Graph DBMS

Embeddable relational database for web apps written in pure JavaScript

A hybrid cloud data analytics software platform (Teradata Vantage)

Primary database model

Secondary database models

Document store
Graph DBMS
Spatial DBMS
Time Series DBMS

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

Score	1.53
Rank	#152	Overall
	#15	Graph DBMS

Score	1.05
Rank	#186	Overall
	#86	Relational DBMS

Score	0.17
Rank	#335	Overall
	#31	Graph DBMS

Score	0.33
Rank	#286	Overall
	#131	Relational DBMS

Score	44.87
Rank	#22	Overall
	#15	Relational DBMS

Website

dgraph.io

www.gbase.cn

github.com/hugegraph
hugegraph.apache.org

google.github.io/lovefield

www.teradata.com

Technical documentation

dgraph.io/docs

hugegraph.apache.org/docs

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

docs.teradata.com

Developer

Dgraph Labs, Inc.

General Data Technology Co., Ltd.

Baidu

Google

Teradata

Initial release

2016

2004

2018

2014

1984

Current release

GBase 8a, GBase 8s, GBase 8c

0.9

2.1.12, February 2017

Teradata Vantage 1.0 MU2, January 2019

License

Commercial or Open Source

Open Source

Apache 2.0

commercial

Open Source

Apache Version 2.0

Open Source

Apache 2.0

commercial

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

C, Java, Python

Java

JavaScript

Server operating systems

Linux
OS X
Windows

Linux

Linux
macOS
Unix

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

tested with Chrome, Firefox, IE, Safari

hosted
Linux

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.

yes

Secondary indexes

yes

also supports composite index and range index

yes

Join-index to prejoin tables, aggregate index, sparse index, hash index

SQL

Support of SQL

Standard with numerous extensions

SQL-like query language

via JavaScript builder pattern

yes

SQL 2016 + extensions

APIs and other access methods

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

ADO.NET
C API
JDBC
ODBC

Java API
RESTful HTTP API
TinkerPop Gremlin

.NET Client API
HTTP REST
JDBC
JMS Adapter
ODBC
OLE DB

Supported programming languages

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

Groovy
Java
Python

JavaScript

C
C++
Cobol
Java (JDBC-ODBC)
Perl
PL/1
Python
R
Ruby

Server-side scripts

Stored procedures

user defined functions

asynchronous Gremlin script jobs

yes

UDFs, stored procedures, table functions in parallel

Triggers

yes

Using read-only observers

yes

Partitioning methods

Methods for storing different data on different nodes

yes

horizontal partitioning (by range, list and hash) and vertical partitioning

yes

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

none

Sharding

Hashing

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

Multi-source replication
Source-replica replication

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

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

yes

In-memory capabilities

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

yes

using MemoryDB

yes

User concepts

Access control

Planned for future releases

yes

Users, roles and permissions

fine grained access rights according to SQL-standard

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More resources

DB-Engines blog posts

Teradata is the most popular data warehouse DBMS
2 April 2013, Paul Andlinger

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