DBMS > IBM Db2 Event Store vs. Microsoft Azure Cosmos DB vs. OpenQM vs. PouchDB

System Properties Comparison IBM Db2 Event Store vs. Microsoft Azure Cosmos DB vs. OpenQM vs. PouchDB

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Editorial information provided by DB-Engines

Name

Description

Distributed Event Store optimized for Internet of Things use cases

Globally distributed, horizontally scalable, multi-model database service

QpenQM is a high-performance, self-tuning, multi-value DBMS

JavaScript DBMS with an API inspired by CouchDB

Primary database model

Event Store
Time Series DBMS

Document store
Graph DBMS
Key-value store
Wide column store

Multivalue DBMS

Document store

Secondary database models

Spatial DBMS

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

Score	0.19
Rank	#323	Overall
	#2	Event Stores
	#28	Time Series DBMS

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

Score	0.27
Rank	#298	Overall
	#10	Multivalue DBMS

Score	2.28
Rank	#115	Overall
	#21	Document stores

Website

www.ibm.com/products/db2-event-store

azure.microsoft.com/services/cosmos-db

www.rocketsoftware.com/products/rocket-multivalue-application-development-platform/rocket-open-qm

pouchdb.com

Technical documentation

www.ibm.com/docs/en/db2-event-store

learn.microsoft.com/azure/cosmos-db

pouchdb.com/guides

Developer

IBM

Microsoft

Rocket Software, originally Martin Phillips

Apache Software Foundation

Initial release

2017

2014

1993

2012

Current release

2.0

3.4-12

7.1.1, June 2019

License

Commercial or Open Source

commercial

free developer edition available

commercial

Open Source

GPLv2, extended commercial license available

Open Source

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

C and C++

JavaScript

Server operating systems

Linux

Linux, macOS, Windows for the developer addition

hosted

AIX
FreeBSD
Linux
macOS
Raspberry Pi
Solaris
Windows

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

Data scheme

yes

schema-free

yes

with some exceptions

schema-free

Typing

predefined data types such as float or date

yes

JSON types

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

via views

SQL

Support of SQL

yes

through the embedded Spark runtime

SQL-like query language

APIs and other access methods

ADO.NET
DB2 Connect
JDBC
ODBC
RESTful HTTP API

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

HTTP REST

only for PouchDB Server
JavaScript API

Supported programming languages

C
C#
C++
Cobol
Delphi
Fortran
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
R
Ruby
Scala
Visual Basic

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

.Net
Basic
C
Java
Objective C
PHP
Python

JavaScript

Server-side scripts

Stored procedures

yes

JavaScript

yes

View functions in JavaScript

Triggers

JavaScript

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

Implicit feature of the cloud service

yes

Sharding

with a proxy-based framework, named couchdb-lounge

Replication methods

Methods for redundantly storing data on multiple nodes

Active-active shard replication

yes

Implicit feature of the cloud service

yes

Multi-source replication

also with CouchDB databases
Source-replica replication

also with CouchDB databases

MapReduce

Offers an API for user-defined Map/Reduce methods

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

Eventual Consistency

Foreign keys

Referential integrity

Transaction concepts

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

Multi-item ACID transactions with snapshot isolation within a partition

ACID

Concurrency

Support for concurrent manipulation of data

No - written data is immutable

yes

Durability

Support for making data persistent

Yes - Synchronous writes to local disk combined with replication and asynchronous writes in parquet format to permanent shared storage

yes

by using IndexedDB, WebSQL or LevelDB as backend

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

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