DBMS > Amazon DocumentDB vs. IBM Cloudant vs. Sadas Engine vs. Yanza

System Properties Comparison Amazon DocumentDB vs. IBM Cloudant vs. Sadas Engine vs. Yanza

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Editorial information provided by DB-Engines

Name

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

Description

Fast, scalable, highly available, and fully managed MongoDB-compatible database service

Database as a Service offering based on Apache CouchDB

SADAS Engine is a columnar DBMS specifically designed for high performance in data warehouse environments

Time Series DBMS for IoT Applications

Primary database model

Document store

Relational DBMS

Time Series DBMS

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

Score	1.91
Rank	#132	Overall
	#24	Document stores

Score	2.68
Rank	#106	Overall
	#20	Document stores

Score	0.00
Rank	#383	Overall
	#158	Relational DBMS

Website

aws.amazon.com/documentdb

www.ibm.com/products/cloudant

www.sadasengine.com

yanza.com

Technical documentation

aws.amazon.com/documentdb/resources

cloud.ibm.com/docs/Cloudant

www.sadasengine.com/en/sadas-engine-download-free-trial-and-documentation/#documentation

Developer

IBM, Apache Software Foundation

IBM acquired Cloudant in February 2014

SADAS s.r.l.

Yanza

Initial release

2019

2010

2006

2015

Current release

8.0

License

Commercial or Open Source

commercial

free trial version 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

Erlang

C++

Server operating systems

hosted

AIX
Linux
Windows

Windows

Data scheme

schema-free

yes

schema-free

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.

Secondary indexes

yes

SQL

Support of SQL

yes

APIs and other access methods

proprietary protocol using JSON (MongoDB compatible)

RESTful HTTP/JSON API

JDBC
ODBC
Proprietary protocol

HTTP API

Supported programming languages

Go
Java
JavaScript (Node.js)
PHP
Python

C#
Java
JavaScript
Objective-C
PHP
Ruby

.Net
C
C#
C++
Groovy
Java
PHP
Python

any language that supports HTTP calls

Server-side scripts

Stored procedures

View functions (Map-Reduce) in JavaScript

Triggers

yes

Timer and event based

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

horizontal partitioning

none

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-availability zones for high availability, asynchronous replication for up to 15 read replicas

Multi-source replication
Source-replica replication

none

MapReduce

Offers an API for user-defined Map/Reduce methods

may be implemented via Amazon Elastic MapReduce (Amazon EMR)

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency

Immediate Consistency

Foreign keys

Referential integrity

typically not used, however similar functionality with DBRef possible

yes

Transaction concepts

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

Atomic single-document operations

atomic operations within a document possible

Concurrency

Support for concurrent manipulation of data

yes

Optimistic locking

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

managed by 'Learn by Usage'

User concepts

Access control

Access rights for users and roles

Access rights for users can be defined per database

Access rights for users, groups and roles according to SQL-standard

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