DBMS > Dgraph vs. Graph Engine vs. H2GIS vs. Teradata Aster

System Properties Comparison Dgraph vs. Graph Engine vs. H2GIS vs. Teradata Aster

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Editorial information provided by DB-Engines

Name

Teradata Aster has been integrated into other Teradata systems and therefore will be removed from the DB-Engines ranking.

Description

Distributed and scalable native Graph DBMS

A distributed in-memory data processing engine, underpinned by a strongly-typed RAM store and a general distributed computation engine

Spatial extension of H2

Platform for big data analytics on multistructured data sources and types

Primary database model

Graph DBMS

Graph DBMS
Key-value store

Spatial DBMS

Relational DBMS

Secondary database models

Relational DBMS

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

Score	1.53
Rank	#152	Overall
	#15	Graph DBMS

Score	0.67
Rank	#232	Overall
	#21	Graph DBMS
	#34	Key-value stores

Score	0.08
Rank	#368	Overall
	#7	Spatial DBMS

Website

dgraph.io

www.graphengine.io

www.h2gis.org

Technical documentation

dgraph.io/docs

www.graphengine.io/docs/manual

www.h2gis.org/docs/home

Developer

Dgraph Labs, Inc.

Microsoft

CNRS

Teradata

Initial release

2016

2010

2013

2005

License

Commercial or Open Source

Open Source

Apache 2.0

Open Source

MIT License

Open Source

LGPL 3.0

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

.NET and C

Java

Server operating systems

Linux
OS X
Windows

.NET

Linux

Data scheme

schema-free

yes

Flexible Schema (defined schema, partial schema, schema free)

defined schema within the relational store; partial schema or schema free in the Aster File Store

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

in Aster File Store

Secondary indexes

yes

SQL

Support of SQL

yes

APIs and other access methods

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

RESTful HTTP API

ADO.NET
JDBC
ODBC
OLE DB

Supported programming languages

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

C#
C++
F#
Visual Basic

Java

C
C#
C++
Java
Python
R

Server-side scripts

Stored procedures

yes

based on H2

R packages

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

yes

horizontal partitioning

none

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

Synchronous replication via Raft

yes

based on H2

yes

Dimension tables are replicated across all nodes in the cluster. The number of replicas for the file store can be configured.

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

SQL Map-Reduce Framework

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Immediate Consistency or Eventual Consistency depending on configuration

Foreign keys

Referential integrity

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

optional: either by committing a write-ahead log (WAL) to the local persistent storage or by dumping the memory to a persistent storage

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

yes

based on H2

fine grained access rights according to SQL-standard

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More resources

Recent citations in the news

Dgraph on AWS: Setting up a horizontally scalable graph database
1 September 2020, AWS Blog

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