DBMS > Dgraph vs. EsgynDB vs. Teradata vs. Transbase vs. Valentina Server

System Properties Comparison Dgraph vs. EsgynDB vs. Teradata vs. Transbase vs. Valentina Server

Editorial information provided by DB-Engines

Name

Description

Distributed and scalable native Graph DBMS

Enterprise-class SQL-on-Hadoop solution, powered by Apache Trafodion

A hybrid cloud data analytics software platform (Teradata Vantage)

A resource-optimized, high-performance, universally applicable RDBMS

Object-relational database and reports server

Primary database model

Graph DBMS

Relational DBMS

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	1.45
Rank	#156	Overall
	#15	Graph DBMS

Score	0.16
Rank	#329	Overall
	#146	Relational DBMS

Score	45.33
Rank	#21	Overall
	#15	Relational DBMS

Score	0.11
Rank	#341	Overall
	#150	Relational DBMS

Score	0.17
Rank	#327	Overall
	#145	Relational DBMS

Website

dgraph.io

www.esgyn.cn

www.teradata.com

www.transaction.de/en/products/transbase.html

www.valentina-db.net

Technical documentation

dgraph.io/docs

docs.teradata.com

www.transaction.de/en/products/transbase/features.html

valentina-db.com/docs/dokuwiki/v5/doku.php

Developer

Dgraph Labs, Inc.

Esgyn

Teradata

Transaction Software GmbH

Paradigma Software

Initial release

2016

2015

1984

1987

1999

Current release

Teradata Vantage 1.0 MU2, January 2019

Transbase 8.3, 2022

5.7.5

License

Commercial or Open Source

Open Source

Apache 2.0

commercial

free development license

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++, Java

C and C++

Server operating systems

Linux
OS X
Windows

Linux

hosted
Linux

FreeBSD
Linux
macOS
Solaris
Windows

Linux
OS X
Windows

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

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

yes

SQL

Support of SQL

yes

SQL 2016 + extensions

yes

APIs and other access methods

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

ADO.NET
JDBC
ODBC

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

ADO.NET
JDBC
ODBC
Proprietary native API

ODBC

Supported programming languages

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

All languages supporting JDBC/ODBC/ADO.Net

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

C
C#
C++
Java
JavaScript
Kotlin
Objective-C
PHP
Python

.Net
C
C#
C++
Objective-C
PHP
Ruby
Visual Basic
Visual Basic.NET

Server-side scripts

Stored procedures

Java Stored Procedures

yes

UDFs, stored procedures, table functions in parallel

yes

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

yes

Sharding

Hashing

Replication methods

Methods for redundantly storing data on multiple nodes

Synchronous replication via Raft

Multi-source replication between multi datacenters

Multi-source replication
Source-replica replication

Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

yes

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

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

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More resources

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