DBMS > Amazon DocumentDB vs. Greenplum vs. Infobright vs. Transbase

System Properties Comparison Amazon DocumentDB vs. Greenplum vs. Infobright vs. Transbase

Please select another system to include it in the comparison.

Editorial information provided by DB-Engines

Name

Description

Fast, scalable, highly available, and fully managed MongoDB-compatible database service

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.

High performant column-oriented DBMS for analytic workloads using MySQL or PostgreSQL as a frontend

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

Primary database model

Document store

Relational DBMS

Secondary database models

Document store
Spatial DBMS

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

Score	1.91
Rank	#124	Overall
	#22	Document stores

Score	7.71
Rank	#46	Overall
	#29	Relational DBMS

Score	0.88
Rank	#198	Overall
	#92	Relational DBMS

Score	0.05
Rank	#355	Overall
	#150	Relational DBMS

Website

aws.amazon.com/documentdb

greenplum.org

ignitetech.com/softwarelibrary/infobrightdb

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

Technical documentation

aws.amazon.com/documentdb/resources

docs.greenplum.org

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

Developer

Pivotal Software Inc.

Ignite Technologies Inc.; formerly InfoBright Inc.

Transaction Software GmbH

Initial release

2019

2005

1987

Current release

7.0.0, September 2023

Transbase 8.3, 2022

License

Commercial or Open Source

commercial

Open Source

Apache 2.0

commercial

The open source (GPLv2) version did not support inserts/updates/deletes and was discontinued with July 2016

commercial

free development license

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

Providers of DBaaS offerings, please contact us to be listed.

Implementation language

C and C++

Server operating systems

hosted

Linux

Linux
Windows

FreeBSD
Linux
macOS
Solaris
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

since Version 4.2

Secondary indexes

yes

Knowledge Grid Technology used instead

yes

SQL

Support of SQL

yes

APIs and other access methods

proprietary protocol using JSON (MongoDB compatible)

JDBC
ODBC

ADO.NET
JDBC
ODBC

ADO.NET
JDBC
ODBC
Proprietary native API

Supported programming languages

Go
Java
JavaScript (Node.js)
PHP
Python

C
Java
Perl
Python
R

.Net
C
C#
C++
D
Eiffel
Erlang
Haskell
Java
Objective-C
OCaml
Perl
PHP
Python
Ruby
Scheme
Tcl

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

Server-side scripts

Stored procedures

yes

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-availability zones for high availability, asynchronous replication for up to 15 read replicas

Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

may be implemented via Amazon Elastic MapReduce (Amazon EMR)

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Foreign keys

Referential integrity

typically not used, however similar functionality with DBRef possible

yes

Transaction concepts

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

Atomic single-document operations

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

Access rights for users and roles

fine grained access rights according to SQL-standard

exploiting MySQL or PostgreSQL frontend capabilities

fine grained access rights according to SQL-standard

More information provided by the system vendor

We invite representatives of system vendors to contact us for updating and extending the system information,
and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.

Related products and services

We invite representatives of vendors of related products to contact us for presenting information about their offerings here.

More resources

Recent citations in the news

Unlock the power of parallel indexing in Amazon DocumentDB
19 June 2024, AWS Blog

AWS announces Amazon DocumentDB zero-ETL integration with Amazon OpenSearch Service
16 May 2024, AWS Blog

Reduce cost and improve performance by migrating to Amazon DocumentDB 5.0
15 April 2024, AWS Blog

Update your Amazon DocumentDB TLS certificates: Expiring in 2024
28 March 2024, AWS Blog

Unlock the power of Amazon DocumentDB text search with real-world use cases
5 March 2024, AWS Blog

provided by Google News

Chapter 1. Introducing the Greenplum Database
6 December 2018, oreilly.com

VMware Greenplum on AWS: Parallel Postgres for Enterprise Analytics at Scale
9 September 2019, AWS Blog

Greenplum 6 ventures outside the analytic box
19 March 2019, ZDNet

EMC and Greenplum Dress Elephant for IT Parade
8 December 2011, WIRED

EMC Introduces Breakthrough 'Big Data' Computing System
13 October 2010, PR Newswire

provided by Google News

Share this page