DBMS > DuckDB vs. Greenplum vs. H2 vs. Machbase

System Properties Comparison DuckDB vs. Greenplum vs. H2 vs. Machbase

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Editorial information provided by DB-Engines

Name

Description

An embeddable, in-process, column-oriented SQL OLAP RDBMS

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.

Full-featured RDBMS with a small footprint, either embedded into a Java application or used as a database server.

TimeSeries DBMS for AIoT and BigData

Primary database model

Relational DBMS

Time Series DBMS

Secondary database models

Document store
Spatial DBMS

Spatial DBMS

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

Score	1.68
Rank	#153	Overall
	#73	Relational DBMS

Score	11.20
Rank	#45	Overall
	#29	Relational DBMS

Score	8.30
Rank	#54	Overall
	#32	Relational DBMS

Score	0.30
Rank	#307	Overall
	#25	Time Series DBMS

Website

Technical documentation

duckdb.org/docs

docs.greenplum.org

www.h2database.com/html/main.html

machbase.atlassian.net/wiki/spaces/MAN/overview

Developer

Pivotal Software Inc.

Thomas Mueller

Machbase

Initial release

2018

2005

2013

Current release

0.2, August 2020

6.7.1, April 2020

2.1.210, January 2022

V6.5, August 2021

License

Commercial or Open Source

Open Source

MIT License

Open Source

Apache 2.0

Open Source

dual-licence (Mozilla public license, Eclipse public license)

commercial

free test version 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.

Implementation language

C++

Java

Server operating systems

server-less

Linux

All OS with a Java VM

Linux
Windows

Data scheme

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

SQL

Support of SQL

yes

SQL-like query language

APIs and other access methods

CLI Client
JDBC

JDBC
ODBC

HTTP REST
JDBC
ODBC

Supported programming languages

C
C++
Go

3rd party driver
Java
Python
R
Ruby

3rd party driver

C
Java
Perl
Python
R

Java

C
C#
C++
Java
JavaScript
PHP

via ODBC
Python
R

via ODBC
Scala

Server-side scripts

Stored procedures

yes

Java Stored Procedures and User-Defined Functions

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

none

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

none

Source-replica replication

With clustering: 2 database servers on different computers operate on identical copies of a database

selectable replication factor

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, multi-version concurrency control (MVCC)

yes

yes, multi-version concurrency control (MVCC)

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

volatile and lookup table

User concepts

Access control

fine grained access rights according to SQL-standard

simple password-based access control

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