DBMS > BigchainDB vs. DataFS vs. EsgynDB vs. Teradata

System Properties Comparison BigchainDB vs. DataFS vs. EsgynDB vs. Teradata

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Editorial information provided by DB-Engines

Name

Description

BigchainDB is scalable blockchain database offering decentralization, immutability and native assets

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.

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

A hybrid cloud data analytics software platform (Teradata Vantage)

Primary database model

Document store

Object oriented DBMS

Relational DBMS

Secondary database models

Graph DBMS

Document store
Graph DBMS
Spatial DBMS
Time Series DBMS

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

Score	0.76
Rank	#216	Overall
	#36	Document stores

Score	0.02
Rank	#369	Overall
	#18	Object oriented DBMS

Score	0.15
Rank	#325	Overall
	#144	Relational DBMS

Score	41.47
Rank	#22	Overall
	#15	Relational DBMS

Website

Technical documentation

bigchaindb.readthedocs.io/en/latest

dev.mobiland.com/Overview.xsp

docs.teradata.com

Developer

Mobiland AG

Esgyn

Teradata

Initial release

2016

2018

2015

1984

Current release

1.1.263, October 2022

Teradata Vantage 1.0 MU2, January 2019

License

Commercial or Open Source

Open Source

AGPL v3

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

Python

C++, Java

Server operating systems

Linux

Windows

Linux

hosted
Linux

Data scheme

schema-free

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

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

SQL

Support of SQL

yes

SQL 2016 + extensions

APIs and other access methods

CLI Client
RESTful HTTP API

.NET Client API
Proprietary client DLL
WinRT client

ADO.NET
JDBC
ODBC

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

Supported programming languages

Go
Haskell
Java
JavaScript
Python
Ruby

.Net
C
C#
C++
VB.Net

All languages supporting JDBC/ODBC/ADO.Net

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

Server-side scripts

Stored procedures

Java Stored Procedures

yes

UDFs, stored procedures, table functions in parallel

Triggers

no, except callback-events from server when changes happened

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

Proprietary Sharding system

Sharding

Hashing

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor

Multi-source replication between multi datacenters

Multi-source 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

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes,with MongoDB ord RethinkDB

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

yes

Windows-Profile

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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