DBMS > IBM Cloudant vs. Microsoft Access vs. Quasardb vs. Snowflake vs. Vitess

System Properties Comparison IBM Cloudant vs. Microsoft Access vs. Quasardb vs. Snowflake vs. Vitess

Editorial information provided by DB-Engines

Name

Description

Database as a Service offering based on Apache CouchDB

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.)

Distributed, high-performance timeseries database

Cloud-based data warehousing service for structured and semi-structured data

Scalable, distributed, cloud-native DBMS, extending MySQL

Primary database model

Secondary database models

Document store
Spatial DBMS

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

Score	2.68
Rank	#106	Overall
	#20	Document stores

Score	104.92
Rank	#11	Overall
	#8	Relational DBMS

Score	0.14
Rank	#332	Overall
	#29	Time Series DBMS

Score	121.33
Rank	#9	Overall
	#6	Relational DBMS

Score	0.82
Rank	#209	Overall
	#97	Relational DBMS

Website

www.ibm.com/products/cloudant

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

quasar.ai

www.snowflake.com

vitess.io

Technical documentation

cloud.ibm.com/docs/Cloudant

developer.microsoft.com/en-us/access

doc.quasar.ai/master

docs.snowflake.net/manuals/index.html

vitess.io/docs

Developer

IBM, Apache Software Foundation

IBM acquired Cloudant in February 2014

Microsoft

quasardb

Snowflake Computing Inc.

The Linux Foundation, PlanetScale

Initial release

2010

1992

2009

2014

2013

Current release

1902 (16.0.11328.20222), March 2019

3.14.1, January 2024

15.0.2, December 2022

License

Commercial or Open Source

commercial

Bundled with Microsoft Office

commercial

Free community edition, Non-profit organizations and non-commercial usage are eligible for free licenses

commercial

Open Source

Apache Version 2.0, commercial licenses available

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

Erlang

C++

Server operating systems

hosted

Windows

Not a real database server, but making use of DLLs

BSD
Linux
OS X
Windows

hosted

Docker
Linux
macOS

Data scheme

schema-free

yes

schema-free

yes

support of semi-structured data formats (JSON, XML, Avro)

yes

Typing

predefined data types such as float or date

yes

integer and binary

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

with tags

yes

SQL

Support of SQL

yes

but not compliant to any SQL standard

SQL-like query language

yes

with proprietary extensions

APIs and other access methods

RESTful HTTP/JSON API

ADO.NET
DAO
ODBC
OLE DB

HTTP API

CLI Client
JDBC
ODBC

ADO.NET
JDBC
MySQL protocol
ODBC

Supported programming languages

C#
Java
JavaScript
Objective-C
PHP
Ruby

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

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

JavaScript (Node.js)
Python

Ada
C
C#
C++
D
Delphi
Eiffel
Erlang
Haskell
Java
JavaScript (Node.js)
Objective-C
OCaml
Perl
PHP
Python
Ruby
Scheme
Tcl

Server-side scripts

Stored procedures

View functions (Map-Reduce) in JavaScript

yes

since Access 2010 using the ACE-engine

user defined functions

yes

proprietary syntax

Triggers

yes

since Access 2010 using the ACE-engine

similar concept for controling cloud resources

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

Sharding

consistent hashing

yes

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication
Source-replica replication

none

Source-replica replication with selectable replication factor

yes

Multi-source replication
Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

with Hadoop integration

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency

Immediate Consistency

Eventual Consistency across shards
Immediate Consistency within a shard

Foreign keys

Referential integrity

yes

not for MyISAM storage engine

Transaction concepts

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

atomic operations within a document possible

ACID

but no files for transaction logging

ACID

ACID at shard level

Concurrency

Support for concurrent manipulation of data

yes

Optimistic locking

yes

table locks or row locks depending on storage engine

Durability

Support for making data persistent

yes

but no files for transaction logging

yes

by using LevelDB

yes

In-memory capabilities

Is there an option to define some or all structures to be held in-memory only.

yes

Transient mode

yes

User concepts

Access control

Access rights for users can be defined per database

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

Cryptographically strong user authentication and audit trail

Users with fine-grained authorization concept, user roles and pluggable authentication

Users with fine-grained authorization concept

no user groups or roles

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