DBMS > Microsoft Azure Cosmos DB vs. Microsoft Azure Synapse Analytics vs. Oracle Rdb vs. Sadas Engine vs. SiriDB

System Properties Comparison Microsoft Azure Cosmos DB vs. Microsoft Azure Synapse Analytics vs. Oracle Rdb vs. Sadas Engine vs. SiriDB

Editorial information provided by DB-Engines

Name

Description

Globally distributed, horizontally scalable, multi-model database service

Elastic, large scale data warehouse service leveraging the broad eco-system of SQL Server

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

Open Source Time Series DBMS

Primary database model

Document store
Graph DBMS
Key-value store
Wide column store

Relational DBMS

Time Series DBMS

Secondary database models

Spatial DBMS

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

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

Score	22.71
Rank	#30	Overall
	#18	Relational DBMS

Score	1.08
Rank	#187	Overall
	#85	Relational DBMS

Score	0.03
Rank	#379	Overall
	#156	Relational DBMS

Score	0.11
Rank	#346	Overall
	#32	Time Series DBMS

Website

azure.microsoft.com/services/cosmos-db

azure.microsoft.com/services/synapse-analytics

www.oracle.com/database/technologies/related/rdb.html

www.sadasengine.com

siridb.com

Technical documentation

learn.microsoft.com/azure/cosmos-db

docs.microsoft.com/azure/synapse-analytics

www.oracle.com/database/technologies/related/rdb-doc.html

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

docs.siridb.com

Developer

Microsoft

Oracle, originally developed by Digital Equipment Corporation (DEC)

SADAS s.r.l.

Cesbit

Initial release

2014

2016

1984

2006

2017

Current release

7.4.1.1, 2021

8.0

License

Commercial or Open Source

commercial

free trial version available

Open Source

MIT License

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++

Server operating systems

hosted

HP Open VMS

AIX
Linux
Windows

Linux

Data scheme

schema-free

yes

Flexible Schema (defined schema, partial schema, schema free)

yes

Typing

predefined data types such as float or date

yes

JSON types

yes

Numeric data

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

All properties auto-indexed by default

yes

SQL

Support of SQL

SQL-like query language

yes

APIs and other access methods

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

ADO.NET
JDBC
ODBC

JDBC
ODBC
Proprietary protocol

HTTP API

Supported programming languages

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

C#
Java
PHP

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

C
C++
Go
Java
JavaScript (Node.js)
PHP
Python
R

Server-side scripts

Stored procedures

JavaScript

Transact SQL

Triggers

JavaScript

Partitioning methods

Methods for storing different data on different nodes

Sharding

Implicit feature of the cloud service

Sharding, horizontal partitioning

horizontal partitioning

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Implicit feature of the cloud service

yes

none

yes

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

Foreign keys

Referential integrity

docs.microsoft.com/en-us/azure/synapse-analytics/sql-data-warehouse/sql-data-warehouse-table-constraints

yes

Transaction concepts

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

Multi-item ACID transactions with snapshot isolation within a partition

ACID

yes, on a single node

Concurrency

Support for concurrent manipulation of data

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'

yes

User concepts

Access control

Access rights can be defined down to the item level

yes

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

simple rights management via user accounts

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