DBMS > Alibaba Cloud Table Store vs. Microsoft Azure Cosmos DB vs. Microsoft SQL Server vs. OrientDB vs. Yaacomo

System Properties Comparison Alibaba Cloud Table Store vs. Microsoft Azure Cosmos DB vs. Microsoft SQL Server vs. OrientDB vs. Yaacomo

Editorial information provided by DB-Engines

Name

Yaacomo seems to be discontinued and is removed from the DB-Engines ranking

Description

A fully managed Wide Column Store for large quantities of semi-structured data with real-time access

Globally distributed, horizontally scalable, multi-model database service

Microsofts flagship relational DBMS

Multi-model DBMS (Document, Graph, Key/Value)

OpenCL based in-memory RDBMS, designed for efficiently utilizing the hardware via parallel computing

Primary database model

Wide column store

Document store
Graph DBMS
Key-value store
Wide column store

Relational DBMS

Document store
Graph DBMS
Key-value store

Relational DBMS

Secondary database models

Spatial DBMS

Document store
Graph DBMS
Spatial DBMS

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

Score	0.26
Rank	#301	Overall
	#12	Wide column stores

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

Score	824.29
Rank	#3	Overall
	#3	Relational DBMS

Score	3.19
Rank	#93	Overall
	#16	Document stores
	#7	Graph DBMS
	#14	Key-value stores

Website

www.alibabacloud.com/product/table-store

azure.microsoft.com/services/cosmos-db

www.microsoft.com/en-us/sql-server

orientdb.org

yaacomo.com

Technical documentation

www.alibabacloud.com/help/en/tablestore

learn.microsoft.com/azure/cosmos-db

learn.microsoft.com/en-US/sql/sql-server

www.orientdb.com/docs/last/index.html

Developer

Alibaba

Microsoft

OrientDB LTD; CallidusCloud; SAP

Q2WEB GmbH

Initial release

2016

2014

1989

2010

2009

Current release

SQL Server 2022, November 2022

3.2.29, March 2024

License

Commercial or Open Source

commercial

restricted free version is available

Open Source

Apache version 2

commercial

Cloud-based only

Only available as a cloud service

yes

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Implementation language

C++

Java

Server operating systems

hosted

Linux
Windows

All OS with a Java JDK (>= JDK 6)

Android
Linux
Windows

Data scheme

schema-free

yes

schema-free

Schema can be enforced for whole record ("schema-full") or for some fields only ("schema-hybrid")

yes

Typing

predefined data types such as float or date

yes

JSON types

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

Secondary indexes

yes

All properties auto-indexed by default

yes

SQL

Support of SQL

SQL-like query language

yes

SQL-like query language, no joins

yes

APIs and other access methods

HTTP API

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

ADO.NET
JDBC
ODBC
OLE DB
Tabular Data Stream (TDS)

Tinkerpop technology stack with Blueprints, Gremlin, Pipes
Java API
RESTful HTTP/JSON API

JDBC
ODBC

Supported programming languages

Java
Python

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

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

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

Server-side scripts

Stored procedures

JavaScript

Transact SQL, .NET languages, R, Python and (with SQL Server 2019) Java

Java, Javascript

Triggers

JavaScript

yes

Hooks

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

Implicit feature of the cloud service

Sharding

Implicit feature of the cloud service

tables can be distributed across several files (horizontal partitioning); sharding through federation

Sharding

horizontal partitioning

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, but depending on the SQL-Server Edition

Multi-source replication

Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

with Hadoop integration

Integration with Hadoop/HDInsight on Azure*

could be achieved with distributed queries

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

Foreign keys

Referential integrity

yes

relationship in graphs

yes

Transaction concepts

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

Atomic single-row operations

Multi-item ACID transactions with snapshot isolation within a partition

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

Access rights based on subaccounts and tokens

Access rights can be defined down to the item level

fine grained access rights according to SQL-standard

Access rights for users and roles; record level security configurable

fine grained access rights according to SQL-standard

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