DBMS > BigchainDB vs. Greenplum vs. OrigoDB vs. PostgreSQL vs. STSdb

System Properties Comparison BigchainDB vs. Greenplum vs. OrigoDB vs. PostgreSQL vs. STSdb

Editorial information provided by DB-Engines

Name

Description

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

Analytic Database platform built on PostgreSQL. Full name is Pivotal Greenplum Database

A logical database in Greenplum is an array of individual PostgreSQL databases working together to present a single database image.

A fully ACID in-memory object graph database

Widely used open source RDBMS

Developed as objectoriented DBMS (Postgres), gradually enhanced with 'standards' like SQL

Key-Value Store with special method for indexing

optimized for high performance using a special indexing method

Primary database model

Document store

Relational DBMS

Document store
Object oriented DBMS

Relational DBMS

with object oriented extensions, e.g.: user defined types/functions and inheritance. Handling of key/value pairs with hstore module.

Key-value store

Secondary database models

Document store
Spatial DBMS

Document store
Graph DBMS

with Apache Age
Spatial DBMS
Vector DBMS

with pgvector extension

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

Score	0.85
Rank	#208	Overall
	#35	Document stores

Score	8.08
Rank	#48	Overall
	#31	Relational DBMS

Score	0.06
Rank	#380	Overall
	#50	Document stores
	#18	Object oriented DBMS

Score	636.25
Rank	#4	Overall
	#4	Relational DBMS

Score	0.10
Rank	#357	Overall
	#51	Key-value stores

Website

github.com/STSSoft/STSdb4

Technical documentation

bigchaindb.readthedocs.io/en/latest

docs.greenplum.org

origodb.com/docs

www.postgresql.org/docs

Developer

Pivotal Software Inc.

Robert Friberg et al

PostgreSQL Global Development Group

www.postgresql.org/developer

STS Soft SC

Initial release

2016

2005

2009

under the name LiveDB

1989

1989: Postgres, 1996: PostgreSQL

2011

Current release

7.0.0, September 2023

16.3, May 2024

4.0.8, September 2015

License

Commercial or Open Source

Open Source

AGPL v3

Open Source

Apache 2.0

Open Source

BSD

Open Source

GPLv2, commercial license available

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.

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Implementation language

Python

Server operating systems

Linux

Linux
Windows

FreeBSD
HP-UX
Linux
NetBSD
OpenBSD
OS X
Solaris
Unix
Windows

Windows

Data scheme

schema-free

yes

Typing

predefined data types such as float or date

yes

User defined using .NET types and collections

yes

primitive types and user defined types (classes)

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

since Version 4.2

can be achieved using .NET

yes

specific XML-type available, but no XML query functionality.

Secondary indexes

yes

SQL

Support of SQL

yes

standard with numerous extensions

APIs and other access methods

CLI Client
RESTful HTTP API

JDBC
ODBC

.NET Client API
HTTP API
LINQ

ADO.NET
JDBC
native C library
ODBC
streaming API for large objects

.NET Client API

Supported programming languages

Go
Haskell
Java
JavaScript
Python
Ruby

C
Java
Perl
Python
R

.Net

.Net
C
C++
Delphi
Java

JDBC
JavaScript (Node.js)
Perl
PHP
Python
Tcl

C#
Java

Server-side scripts

Stored procedures

yes

user defined functions

realized in proprietary language PL/pgSQL or with common languages like Perl, Python, Tcl etc.

Triggers

yes

Domain Events

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

horizontal partitioning

client side managed; servers are not synchronized

partitioning by range, list and (since PostgreSQL 11) by hash

none

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor

Source-replica replication

other methods possible by using 3rd party extensions

none

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

depending on model

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

Write ahead log

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

fine grained access rights according to SQL-standard

Role based authorization

fine grained access rights according to SQL-standard

More information provided by the system vendor

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