DBMS > IBM Db2 vs. Microsoft Azure Cosmos DB vs. OpenEdge vs. SQLite vs. ToroDB

System Properties Comparison IBM Db2 vs. Microsoft Azure Cosmos DB vs. OpenEdge vs. SQLite vs. ToroDB

Editorial information provided by DB-Engines

Name

ToroDB seems to be discontinued. Therefore it is excluded from the DB-Engines Ranking.

Description

Common in IBM host environments, 2 different versions for host and Windows/Linux

Globally distributed, horizontally scalable, multi-model database service

Application development environment with integrated database management system

Widely used embeddable, in-process RDBMS

A MongoDB-compatible JSON document store, built on top of PostgreSQL

Primary database model

Relational DBMS

Since Version 10.5 support for JSON/BSON documents compatible with MongoDB

Document store
Graph DBMS
Key-value store
Wide column store

Relational DBMS

Document store

Secondary database models

Document store
RDF store

in Db2 LUW (Linux, Unix, Windows)
Spatial DBMS

with Db2 Spatial Extender

Spatial DBMS

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

Score	128.46
Rank	#8	Overall
	#5	Relational DBMS

Score	29.04
Rank	#27	Overall
	#4	Document stores
	#2	Graph DBMS
	#3	Key-value stores
	#3	Wide column stores

Score	3.51
Rank	#86	Overall
	#46	Relational DBMS

Score	114.32
Rank	#10	Overall
	#7	Relational DBMS

Website

www.ibm.com/products/db2

azure.microsoft.com/services/cosmos-db

www.progress.com/openedge

www.sqlite.org

github.com/torodb/server

Technical documentation

www.ibm.com/docs/en/db2

learn.microsoft.com/azure/cosmos-db

documentation.progress.com/output/ua/OpenEdge_latest

www.sqlite.org/docs.html

Developer

IBM

Microsoft

Progress Software Corporation

Dwayne Richard Hipp

8Kdata

Initial release

1983

host version

2014

1984

2000

2016

Current release

12.1, October 2016

OpenEdge 12.2, March 2020

3.46.0 (23 May 2024), May 2024

License

Commercial or Open Source

commercial

free version is available

commercial

Open Source

Public Domain

Open Source

AGPL-V3

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

C and C++

Java

Server operating systems

AIX
HP-UX
Linux
Solaris
Windows
z/OS

hosted

AIX
HP-UX
Linux
Solaris
Windows

server-less

All OS with a Java 7 VM

Data scheme

yes

schema-free

yes

dynamic column types

schema-free

Typing

predefined data types such as float or date

yes

JSON types

yes

not rigid because of 'dynamic typing' concept.

yes

string, integer, double, boolean, date, object_id

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

Secondary indexes

yes

All properties auto-indexed by default

yes

SQL

Support of SQL

yes

SQL-like query language

yes

close to SQL 92

yes

SQL-92 is not fully supported

APIs and other access methods

ADO.NET
JDBC
JSON style queries

MongoDB compatible
ODBC
XQuery

DocumentDB API
Graph API (Gremlin)
MongoDB API
RESTful HTTP API
Table API

JDBC
ODBC

ADO.NET

inofficial driver
JDBC

inofficial driver
ODBC

inofficial driver

Supported programming languages

C
C#
C++
Cobol
Delphi
Fortran
Java
Perl
PHP
Python
Ruby
Visual Basic

.Net
C#
Java
JavaScript
JavaScript (Node.js)
MongoDB client drivers written for various programming languages
Python

Progress proprietary ABL (Advanced Business Language)

Actionscript
Ada
Basic
C
C#
C++
D
Delphi
Forth
Fortran
Haskell
Java
JavaScript
Lisp
Lua
MatLab
Objective-C
OCaml
Perl
PHP
PL/SQL
Python
R
Ruby
Scala
Scheme
Smalltalk
Tcl

Server-side scripts

Stored procedures

yes

JavaScript

yes

Triggers

yes

JavaScript

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

only with Windows/Unix/Linux Version

Sharding

Implicit feature of the cloud service

horizontal partitioning

since Version 11.4

none

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

yes

with separate tools (MQ, InfoSphere)

yes

Implicit feature of the cloud service

Source-replica replication

none

Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

with Hadoop integration

Integration with Hadoop/HDInsight on Azure*

Consistency concepts

Methods to ensure consistency in a distributed system

Bounded Staleness
Consistent Prefix
Eventual Consistency
Immediate Consistency

Consistency level configurable on request level
Session Consistency

Immediate Consistency

Eventual Consistency
Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

Multi-item ACID transactions with snapshot isolation within a partition

ACID

Concurrency

Support for concurrent manipulation of data

yes

via file-system locks

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

Users and groups

Access rights for users and roles

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