DBMS > Citus vs. EventStoreDB vs. OpenEdge vs. SAP SQL Anywhere

System Properties Comparison Citus vs. EventStoreDB vs. OpenEdge vs. SAP SQL Anywhere

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Editorial information provided by DB-Engines

Name

Description

Scalable hybrid operational and analytics RDBMS for big data use cases based on PostgreSQL

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

Application development environment with integrated database management system

RDBMS database and synchronization technologies for server, desktop, remote office, and mobile environments

Primary database model

Relational DBMS

Event Store

Relational DBMS

Secondary database models

Document store

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

Score	2.13
Rank	#117	Overall
	#56	Relational DBMS

Score	1.07
Rank	#181	Overall
	#1	Event Stores

Score	3.69
Rank	#78	Overall
	#42	Relational DBMS

Score	3.50
Rank	#81	Overall
	#44	Relational DBMS

Website

www.citusdata.com

www.eventstore.com

www.progress.com/openedge

www.sap.com/products/technology-platform/sql-anywhere.html

Technical documentation

docs.citusdata.com

developers.eventstore.com

documentation.progress.com/output/ua/OpenEdge_latest

help.sap.com/docs/SAP_SQL_Anywhere

Developer

Event Store Limited

Progress Software Corporation

SAP

formerly Sybase

Initial release

2010

2012

1984

1992

Current release

8.1, December 2018

21.2, February 2021

OpenEdge 12.2, March 2020

17, July 2015

License

Commercial or Open Source

Open Source

AGPL, commercial license also available

Open Source

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

Server operating systems

Linux

Linux
Windows

AIX
HP-UX
Linux
Solaris
Windows

AIX
HP-UX
Linux
OS X
Solaris
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

specific XML type available, but no XML query functionality

yes

Secondary indexes

yes

SQL

Support of SQL

yes

standard, with numerous extensions

yes

close to SQL 92

yes

APIs and other access methods

ADO.NET
JDBC
native C library
ODBC
streaming API for large objects

JDBC
ODBC

ADO.NET
HTTP API
JDBC
ODBC

Supported programming languages

.Net
C
C++
Delphi
Java
JavaScript (Node.js)
Perl
PHP
Python
Tcl

Progress proprietary ABL (Advanced Business Language)

C
C#
C++
Delphi
Java
JavaScript (Node.js)
Perl
PHP
Python
Ruby

Server-side scripts

Stored procedures

user defined functions

realized in proprietary language PL/pgSQL or with common languages like Perl, Python, Tcl etc.

yes

yes, in C/C++, Java, .Net or Perl

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

horizontal partitioning

since Version 11.4

none

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

other methods possible by using 3rd party extensions

Source-replica replication

Database mirroring

MapReduce

Offers an API for user-defined Map/Reduce methods

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.

yes

User concepts

Access control

fine grained access rights according to SQL-standard

Users and groups

fine grained access rights according to SQL-standard

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More resources

Recent citations in the news

Microsoft acquires Citus Data, re-affirming its commitment to Open Source and accelerating Azure PostgreSQL performance and scale
24 January 2019, blogs.microsoft.com

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