DBMS > Microsoft Access vs. Microsoft Azure Cosmos DB vs. Microsoft SQL Server vs. SpaceTime vs. ToroDB

System Properties Comparison Microsoft Access vs. Microsoft Azure Cosmos DB vs. Microsoft SQL Server vs. SpaceTime vs. ToroDB

Editorial information provided by DB-Engines

Name

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

Description

Microsoft Access combines a backend RDBMS (JET / ACE Engine) with a GUI frontend for data manipulation and queries.

The Access frontend is often used for accessing other datasources (DBMS, Excel, etc.)

Globally distributed, horizontally scalable, multi-model database service

Microsofts flagship relational DBMS

SpaceTime is a spatio-temporal DBMS with a focus on performance.

A MongoDB-compatible JSON document store, built on top of PostgreSQL

Primary database model

Relational DBMS

Document store
Graph DBMS
Key-value store
Wide column store

Relational DBMS

Spatial DBMS

Document store

Secondary database models

Spatial DBMS

Document store
Graph DBMS
Spatial DBMS

Relational DBMS

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

Score	104.92
Rank	#11	Overall
	#8	Relational DBMS

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	0.00
Rank	#383	Overall
	#7	Spatial DBMS

Website

www.microsoft.com/en-us/microsoft-365/access

azure.microsoft.com/services/cosmos-db

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

www.mireo.com/spacetime

github.com/torodb/server

Technical documentation

developer.microsoft.com/en-us/access

learn.microsoft.com/azure/cosmos-db

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

Developer

Microsoft

Mireo

8Kdata

Initial release

1992

2014

1989

2020

2016

Current release

1902 (16.0.11328.20222), March 2019

SQL Server 2022, November 2022

License

Commercial or Open Source

commercial

Bundled with Microsoft Office

commercial

restricted free version is available

commercial

Open Source

AGPL-V3

Cloud-based only

Only available as a cloud service

yes

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Implementation language

C++

Java

Server operating systems

Windows

Not a real database server, but making use of DLLs

hosted

Linux
Windows

Linux

All OS with a Java 7 VM

Data scheme

yes

schema-free

yes

schema-free

Typing

predefined data types such as float or date

yes

JSON types

yes

string, integer, double, boolean, date, object_id

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

but not compliant to any SQL standard

SQL-like query language

yes

A subset of ANSI SQL is implemented

APIs and other access methods

ADO.NET
DAO
ODBC
OLE DB

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

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

RESTful HTTP API

Supported programming languages

C
C#
C++
Delphi
Java (JDBC-ODBC)
VBA
Visual Basic.NET

.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

C#
C++
Python

Server-side scripts

Stored procedures

yes

since Access 2010 using the ACE-engine

JavaScript

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

Triggers

yes

since Access 2010 using the ACE-engine

JavaScript

yes

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

Implicit feature of the cloud service

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

Fixed-grid hypercubes

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

none

yes

Implicit feature of the cloud service

yes, but depending on the SQL-Server Edition

Real-time block device replication (DRBD)

Source-replica replication

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

Eventual Consistency
Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

but no files for transaction logging

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

but no files for transaction logging

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

a simple user-level security was built in till version Access 2003

Access rights can be defined down to the item level

fine grained access rights according to SQL-standard

yes

Access rights for users and roles

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