DBMS > Amazon DynamoDB vs. IBM Db2 Event Store vs. Microsoft Azure Cosmos DB vs. OpenQM vs. Yanza

System Properties Comparison Amazon DynamoDB vs. IBM Db2 Event Store vs. Microsoft Azure Cosmos DB vs. OpenQM vs. Yanza

Editorial information provided by DB-Engines

Name

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

Description

Hosted, scalable database service by Amazon with the data stored in Amazons cloud

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

Time Series DBMS for IoT Applications

Primary database model

Document store
Key-value store

Event Store
Time Series DBMS

Document store
Graph DBMS
Key-value store
Wide column store

Multivalue DBMS

Time Series DBMS

Secondary database models

Spatial DBMS

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

Score	77.57
Rank	#16	Overall
	#2	Document stores
	#2	Key-value stores

Score	0.23
Rank	#316	Overall
	#2	Event Stores
	#28	Time Series DBMS

Score	29.85
Rank	#27	Overall
	#4	Document stores
	#2	Graph DBMS
	#3	Key-value stores
	#3	Wide column stores

Score	0.33
Rank	#286	Overall
	#10	Multivalue DBMS

Website

aws.amazon.com/dynamodb

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

yanza.com

Technical documentation

docs.aws.amazon.com/dynamodb

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

learn.microsoft.com/azure/cosmos-db

Developer

Amazon

IBM

Microsoft

Rocket Software, originally Martin Phillips

Yanza

Initial release

2012

2017

2014

1993

2015

Current release

2.0

3.4-12

License

Commercial or Open Source

commercial

free tier for a limited amount of database operations

commercial

free developer edition available

commercial

Open Source

GPLv2, extended commercial license available

commercial

free version available

Cloud-based only

Only available as a cloud service

yes

but mainly used as a service provided by Yanza

DBaaS offerings (sponsored links)

Database as a Service

Providers of DBaaS offerings, please contact us to be listed.

Implementation language

C and C++

Server operating systems

hosted

Linux

Linux, macOS, Windows for the developer addition

hosted

AIX
FreeBSD
Linux
macOS
Raspberry Pi
Solaris
Windows

Windows

Data scheme

schema-free

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

SQL

Support of SQL

yes

through the embedded Spark runtime

SQL-like query language

APIs and other access methods

RESTful HTTP API

ADO.NET
DB2 Connect
JDBC
ODBC
RESTful HTTP API

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

HTTP API

Supported programming languages

.Net
ColdFusion
Erlang
Groovy
Java
JavaScript
Perl
PHP
Python
Ruby

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

any language that supports HTTP calls

Server-side scripts

Stored procedures

yes

JavaScript

yes

Triggers

yes

by integration with AWS Lambda

JavaScript

yes

Timer and event based

Partitioning methods

Methods for storing different data on different nodes

Sharding

Implicit feature of the cloud service

yes

none

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Active-active shard replication

yes

Implicit feature of the cloud service

yes

none

MapReduce

Offers an API for user-defined Map/Reduce methods

may be implemented via Amazon Elastic MapReduce (Amazon EMR)

with Hadoop integration

Integration with Hadoop/HDInsight on Azure*

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency
Immediate Consistency

can be specified for read operations

Eventual Consistency

Bounded Staleness
Consistent Prefix
Eventual Consistency
Immediate Consistency

Consistency level configurable on request level
Session Consistency

Immediate Consistency

Foreign keys

Referential integrity

Transaction concepts

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

ACID

ACID across one or more tables within a single AWS account and region

Multi-item ACID transactions with snapshot isolation within a partition

ACID

Concurrency

Support for concurrent manipulation of data

yes

No - written data is immutable

yes

Durability

Support for making data persistent

yes

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

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 and roles can be defined via the AWS Identity and Access Management (IAM)

fine grained access rights according to SQL-standard

Access rights can be defined down to the item level

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