DBMS > Alibaba Cloud AnalyticDB for MySQL vs. Microsoft Azure Cosmos DB vs. Microsoft Azure SQL Database vs. NCache vs. Stardog

System Properties Comparison Alibaba Cloud AnalyticDB for MySQL vs. Microsoft Azure Cosmos DB vs. Microsoft Azure SQL Database vs. NCache vs. Stardog

Editorial information provided by DB-Engines

Name

Description

A real-time data warehousing service that can process petabytes of data with high concurrency and low latency. It is fully compatible with the MySQL protocol.

Globally distributed, horizontally scalable, multi-model database service

Database as a Service offering with high compatibility to Microsoft SQL Server

Open-Source and Enterprise in-memory Key-Value Store

Enterprise Knowledge Graph platform and graph DBMS with high availability, high performance reasoning, and virtualization

Primary database model

Relational DBMS

Document store
Graph DBMS
Key-value store
Wide column store

Relational DBMS

Key-value store

Graph DBMS
RDF store

Secondary database models

Document store

Spatial DBMS

Document store
Graph DBMS
Spatial DBMS

Document store
Search engine

Using distributed Lucene

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

Score	0.76
Rank	#223	Overall
	#103	Relational DBMS

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

Score	78.40
Rank	#15	Overall
	#10	Relational DBMS

Score	0.98
Rank	#196	Overall
	#29	Key-value stores

Score	2.05
Rank	#129	Overall
	#11	Graph DBMS
	#6	RDF stores

Website

www.alibabacloud.com/product/analyticdb-for-mysql

azure.microsoft.com/services/cosmos-db

azure.microsoft.com/en-us/products/azure-sql/database

www.alachisoft.com/ncache

www.stardog.com

Technical documentation

www.alibabacloud.com/help/doc-detail/93776.htm

learn.microsoft.com/azure/cosmos-db

docs.microsoft.com/en-us/azure/azure-sql

www.alachisoft.com/resources/docs

docs.stardog.com

Developer

Alibaba

Microsoft

Alachisoft

Stardog-Union

Initial release

2014

2010

2005

2010

Current release

V12

5.3.3, April 2024

7.3.0, May 2020

License

Commercial or Open Source

commercial

Open Source

Enterprise Edition available

commercial

60-day fully-featured trial license; 1-year fully-featured non-commercial use license for academics/students

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++

C#, .NET, .NET Core, Java

Java

Server operating systems

hosted

Linux
Windows

Linux
macOS
Windows

Data scheme

yes

schema-free

yes

schema-free

schema-free and OWL/RDFS-schema support

Typing

predefined data types such as float or date

yes

JSON types

yes

partial

Supported data types are Lists, Queues, Hashsets, Dictionary and Counter

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

Import/export of XML data possible

Secondary indexes

yes

All properties auto-indexed by default

yes

supports real-time indexing in full-text and geospatial

SQL

Support of SQL

yes

SQL-like query language

yes

SQL-like query syntax and LINQ for searching the cache. Cache Synchronization with SQL Server using SQL dependency.

Yes, compatible with all major SQL variants through dedicated BI/SQL Server

APIs and other access methods

JDBC
ODBC

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

ADO.NET
JDBC
ODBC

IDistributedCache
JCache
LINQ
Proprietary native API

GraphQL query language
HTTP API
Jena RDF API
OWL
RDF4J API
Sesame REST HTTP Protocol
SNARL
SPARQL
Spring Data
Stardog Studio
TinkerPop 3

Supported programming languages

C#
Java
PHP
Python

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

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

.Net
.Net Core
C#
Java
JavaScript (Node.js)
Python
Scala

.Net
Clojure
Groovy
Java
JavaScript
Python
Ruby

Server-side scripts

Stored procedures

yes

JavaScript

Transact SQL

support for stored procedures with SQL-Server CLR

user defined functions and aggregates, HTTP Server extensions in Java

Triggers

yes

JavaScript

yes

Notifications

yes

via event handlers

Partitioning methods

Methods for storing different data on different nodes

Sharding

Implicit feature of the cloud service

Sharding

Implicit feature of the cloud service

yes

none

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Implicit feature of the cloud service

yes

Implicit feature of the cloud service

yes, with always 3 replicas available

yes, with selectable consistency level

Multi-source replication in HA-Cluster

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

Immediate Consistency

Bounded Staleness
Consistent Prefix
Eventual Consistency
Immediate Consistency

Consistency level configurable on request level
Session Consistency

Immediate Consistency

Eventual Consistency
Immediate Consistency
Strong Eventual Consistency over WAN with Conflict Resolution using Bridge Topology

Immediate Consistency in HA-Cluster

Foreign keys

Referential integrity

yes

relationships in graphs

Transaction concepts

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

ACID

Multi-item ACID transactions with snapshot isolation within a partition

ACID

optimistic locking and pessimistic locking

ACID

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

User concepts

Access control

fine grained access rights according to SQL-standard

Access rights can be defined down to the item level

fine grained access rights according to SQL-standard

Authentication to access the cache via Active Directory/LDAP (possible roles: user, administrator)

Access rights for users and roles

More information provided by the system vendor

Specific characteristics

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Competitive advantages

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Typical application scenarios

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Key customers

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Market metrics

Market Leader in .NET Distributed Caching since 2005.
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Licensing and pricing models

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