DBMS > EventStoreDB vs. Greenplum vs. SWC-DB

System Properties Comparison EventStoreDB vs. Greenplum vs. SWC-DB

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Editorial information provided by DB-Engines

Name

Description

Industrial-strength, open-source database solution built from the ground up for event sourcing.

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 high performance, scalable Wide Column DBMS

Primary database model

Event Store

Relational DBMS

Wide column store

Secondary database models

Document store
Spatial DBMS

Time Series DBMS

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

Score	1.14
Rank	#181	Overall
	#1	Event Stores

Score	9.23
Rank	#47	Overall
	#30	Relational DBMS

Score	0.01
Rank	#387	Overall
	#13	Wide column stores

Website

www.eventstore.com

greenplum.org

github.com/kashirin-alex/swc-db
www.swcdb.org

Technical documentation

developers.eventstore.com

docs.greenplum.org

Developer

Event Store Limited

Pivotal Software Inc.

Alex Kashirin

Initial release

2012

2005

2020

Current release

21.2, February 2021

7.0.0, September 2023

0.5, April 2021

License

Commercial or Open Source

Open Source

Apache 2.0

Open Source

GPL V3

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

C++

Server operating systems

Linux
Windows

Linux

Data scheme

yes

schema-free

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

JDBC
ODBC

Proprietary protocol
Thrift

Supported programming languages

C
Java
Perl
Python
R

C++

Server-side scripts

Stored procedures

yes

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

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

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

In-memory capabilities

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

User concepts

Access control

fine grained access rights according to SQL-standard

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