DBMS > Greenplum vs. OpenQM vs. Qdrant vs. UniData,UniVerse

System Properties Comparison Greenplum vs. OpenQM vs. Qdrant vs. UniData,UniVerse

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Editorial information provided by DB-Engines

Name

Description

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.

QpenQM is a high-performance, self-tuning, multi-value DBMS

A high-performance vector database with neural network or semantic-based matching

MultiValue database and application server with SQL mapping layer and meta database capabilities

Primary database model

Secondary database models

Document store
Spatial DBMS

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

Score	7.71
Rank	#46	Overall
	#29	Relational DBMS

Score	0.28
Rank	#291	Overall
	#10	Multivalue DBMS

Score	1.53
Rank	#145	Overall
	#7	Vector DBMS

Score	2.25
Rank	#112	Overall
	#2	Multivalue DBMS

Website

greenplum.org

www.rocketsoftware.com/products/rocket-multivalue-application-development-platform/rocket-open-qm

github.com/qdrant/qdrant
qdrant.tech

www.rocketsoftware.com/products/rocket-multivalue-application-development-platform/rocket-unidata

Technical documentation

docs.greenplum.org

qdrant.tech/documentation

docs.rocketsoftware.com/bundle?cluster=true&labelkey=unidata&labelkey=prod_unidata

Developer

Pivotal Software Inc.

Rocket Software, originally Martin Phillips

Qdrant

Rocket Software

Initial release

2005

1993

2021

1985

Current release

7.0.0, September 2023

3.4-12

License

Commercial or Open Source

Open Source

Apache 2.0

Open Source

GPLv2, extended commercial license available

Open Source

Apache Version 2.0

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

Rust

Server operating systems

Linux

AIX
FreeBSD
Linux
macOS
Raspberry Pi
Solaris
Windows

Docker
Linux
macOS
Windows

AIX
HP-UX
Linux
Solaris
Windows

Data scheme

yes

with some exceptions

schema-free

Typing

predefined data types such as float or date

yes

Numbers, Strings, Geo, Boolean

optional

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

yes

Secondary indexes

yes

Keywords, numberic ranges, geo, full-text

yes

SQL

Support of SQL

yes

APIs and other access methods

JDBC
ODBC

gRPC
OpenAPI 3.0
RESTful HTTP/JSON API

OpenAPI 3.0

Java API

JPA
JDBC
ODBC
OLE DB
Proprietary protocol
RESTful HTTP API
SOAP-based API

Supported programming languages

C
Java
Perl
Python
R

.Net
Basic
C
Java
Objective C
PHP
Python

.Net
Go
Java
JavaScript (Node.js)
Python
Rust

.Net
Basic

U2 Basic
C
Java

Server-side scripts

Stored procedures

yes

Triggers

yes

U2 Basic

Partitioning methods

Methods for storing different data on different nodes

Sharding

yes

Sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

yes

Collection-level 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

Eventual Consistency, tunable consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

configurable

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

fine grained access rights according to SQL-standard

Access rights can be defined down to the item level

Key-based authentication

Access rights according to SQL-standard and operating system based

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More resources

Recent citations in the news

Chapter 1. Introducing the Greenplum Database
6 December 2018, O'Reilly Media

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

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