DBMS > Greenplum vs. Lovefield vs. openGemini vs. Snowflake

System Properties Comparison Greenplum vs. Lovefield vs. openGemini vs. Snowflake

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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.

Embeddable relational database for web apps written in pure JavaScript

An open source distributed Time Series DBMS with high concurrency, high performance, and high scalability

Cloud-based data warehousing service for structured and semi-structured data

Primary database model

Relational DBMS

Time Series DBMS

Relational DBMS

Secondary database models

Document store
Spatial DBMS

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

Score	8.08
Rank	#48	Overall
	#31	Relational DBMS

Score	0.33
Rank	#286	Overall
	#131	Relational DBMS

Score	0.09
Rank	#361	Overall
	#37	Time Series DBMS

Score	130.36
Rank	#8	Overall
	#5	Relational DBMS

Website

greenplum.org

google.github.io/lovefield

www.opengemini.org
github.com/openGemini

www.snowflake.com

Technical documentation

docs.greenplum.org

github.com/google/lovefield/blob/master/docs/spec_index.md

docs.opengemini.org/guide

docs.snowflake.net/manuals/index.html

Developer

Pivotal Software Inc.

Google

Huawei and openGemini community

Snowflake Computing Inc.

Initial release

2005

2014

2022

2014

Current release

7.0.0, September 2023

2.1.12, February 2017

1.1, July 2023

License

Commercial or Open Source

Open Source

Apache 2.0

Open Source

Apache 2.0

Open Source

Apache Version 2.0

commercial

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

JavaScript

Server operating systems

Linux

server-less, requires a JavaScript environment (browser, Node.js)

tested with Chrome, Firefox, IE, Safari

Linux
Windows

hosted

Data scheme

yes

schema-free

yes

support of semi-structured data formats (JSON, XML, Avro)

Typing

predefined data types such as float or date

yes

Integer, Float, Boolean, String

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

yes

Secondary indexes

yes

SQL

Support of SQL

yes

SQL-like query language

via JavaScript builder pattern

SQL-like query language

yes

APIs and other access methods

JDBC
ODBC

HTTP REST

CLI Client
JDBC
ODBC

Supported programming languages

C
Java
Perl
Python
R

JavaScript

C
C++
Go
Java
JavaScript (Node.js)
Python
Rust

JavaScript (Node.js)
Python

Server-side scripts

Stored procedures

yes

user defined functions

Triggers

yes

Using read-only observers

similar concept for controling cloud resources

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

Sharding

yes

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

none

yes

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

yes, by using IndexedDB or the cloud service Firebase Realtime Database

yes

In-memory capabilities

Is there an option to define some or all structures to be held in-memory only.

yes

using MemoryDB

yes

User concepts

Access control

fine grained access rights according to SQL-standard

Administrators and common users accounts

Users with fine-grained authorization concept, user roles and pluggable authentication

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