DBMS > IBM Cloudant vs. ITTIA vs. Microsoft Azure Cosmos DB vs. OpenEdge vs. RavenDB

System Properties Comparison IBM Cloudant vs. ITTIA vs. Microsoft Azure Cosmos DB vs. OpenEdge vs. RavenDB

Editorial information provided by DB-Engines

Name

Description

Database as a Service offering based on Apache CouchDB

Edge Time Series DBMS with Real-Time Stream Processing

Globally distributed, horizontally scalable, multi-model database service

Application development environment with integrated database management system

Open Source Operational and Transactional Enterprise NoSQL Document Database

Primary database model

Document store

Time Series DBMS

Document store
Graph DBMS
Key-value store
Wide column store

Relational DBMS

Document store

Secondary database models

Relational DBMS

Spatial DBMS

Graph DBMS
Spatial DBMS
Time Series DBMS

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

Score	2.68
Rank	#106	Overall
	#20	Document stores

Score	0.39
Rank	#273	Overall
	#24	Time Series 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	2.92
Rank	#101	Overall
	#18	Document stores

Website

www.ibm.com/products/cloudant

www.ittia.com

azure.microsoft.com/services/cosmos-db

www.progress.com/openedge

ravendb.net

Technical documentation

cloud.ibm.com/docs/Cloudant

learn.microsoft.com/azure/cosmos-db

documentation.progress.com/output/ua/OpenEdge_latest

ravendb.net/docs

Developer

IBM, Apache Software Foundation

IBM acquired Cloudant in February 2014

ITTIA L.L.C.

Microsoft

Progress Software Corporation

Hibernating Rhinos

Initial release

2010

2007

2014

1984

2010

Current release

8.7

OpenEdge 12.2, March 2020

5.4, July 2022

License

Commercial or Open Source

commercial

Open Source

AGPL version 3, commercial license available

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

Erlang

C and C++

Server operating systems

hosted

Linux
Windows

hosted

AIX
HP-UX
Linux
Solaris
Windows

Linux
macOS
Raspberry Pi
Windows

Data scheme

schema-free

Fixed schema

schema-free

yes

schema-free

Typing

predefined data types such as float or date

Float/Blob/Integer/String/Unicode/Date/Time/Timestamp/Interval

yes

JSON types

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

Secondary indexes

yes

All properties auto-indexed by default

yes

SQL

Support of SQL

yes

SQL-like query language

yes

close to SQL 92

SQL-like query language (RQL)

APIs and other access methods

RESTful HTTP/JSON API

JDBC
ODBC
RESTful HTTP API
WebSocket

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

JDBC
ODBC

.NET Client API
F# Client API
Go Client API
Java Client API
NodeJS Client API
PHP Client API
Python Client API
RESTful HTTP API

Supported programming languages

C#
Java
JavaScript
Objective-C
PHP
Ruby

C
C++
JavaScript (Node.js)
Python

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

Progress proprietary ABL (Advanced Business Language)

.Net
C#
F#
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby

Server-side scripts

Stored procedures

View functions (Map-Reduce) in JavaScript

yes

JavaScript

yes

Triggers

yes

JavaScript

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

Implicit feature of the cloud service

horizontal partitioning

since Version 11.4

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication
Source-replica replication

yes

Implicit feature of the cloud service

Source-replica replication

Multi-source replication

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

with Hadoop integration

Integration with Hadoop/HDInsight on Azure*

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency

Bounded Staleness
Consistent Prefix
Eventual Consistency
Immediate Consistency

Consistency level configurable on request level
Session Consistency

Immediate Consistency

Default ACID transactions on the local node (eventually consistent across the cluster). Atomic operations with cluster-wide ACID transactions. Eventual consistency for indexes and full-text search indexes.

Foreign keys

Referential integrity

yes

Transaction concepts

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

atomic operations within a document possible

yes

Multi-item ACID transactions with snapshot isolation within a partition

ACID

ACID, Cluster-wide transaction available

Concurrency

Support for concurrent manipulation of data

yes

Optimistic locking

yes, multi-version concurrency control (MVCC)

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

Access rights for users can be defined per database

Database file passwords

Access rights can be defined down to the item level

Users and groups

Authorization levels configured per client per database

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