DBMS > Hive vs. IBM Cloudant vs. Microsoft Access vs. Microsoft Azure Cosmos DB vs. Quasardb

System Properties Comparison Hive vs. IBM Cloudant vs. Microsoft Access vs. Microsoft Azure Cosmos DB vs. Quasardb

Editorial information provided by DB-Engines

Name

Description

data warehouse software for querying and managing large distributed datasets, built on Hadoop

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.)

Globally distributed, horizontally scalable, multi-model database service

Distributed, high-performance timeseries database

Primary database model

Relational DBMS

Document store

Relational DBMS

Document store
Graph DBMS
Key-value store
Wide column store

Time Series DBMS

Secondary database models

Spatial DBMS

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

Score	62.59
Rank	#18	Overall
	#12	Relational DBMS

Score	2.73
Rank	#108	Overall
	#20	Document stores

Score	105.40
Rank	#11	Overall
	#8	Relational DBMS

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

Score	0.19
Rank	#327	Overall
	#30	Time Series DBMS

Website

hive.apache.org

www.ibm.com/products/cloudant

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

azure.microsoft.com/services/cosmos-db

quasar.ai

Technical documentation

cwiki.apache.org/confluence/display/Hive/Home

cloud.ibm.com/docs/Cloudant

developer.microsoft.com/en-us/access

learn.microsoft.com/azure/cosmos-db

doc.quasar.ai/master

Developer

Apache Software Foundation

initially developed by Facebook

IBM, Apache Software Foundation

IBM acquired Cloudant in February 2014

Microsoft

quasardb

Initial release

2012

2010

1992

2014

2009

Current release

3.1.3, April 2022

1902 (16.0.11328.20222), March 2019

3.14.1, January 2024

License

Commercial or Open Source

Open Source

Apache Version 2

commercial

Bundled with Microsoft Office

commercial

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

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

Java

Erlang

C++

Server operating systems

All OS with a Java VM

hosted

Windows

Not a real database server, but making use of DLLs

hosted

BSD
Linux
OS X
Windows

Data scheme

yes

schema-free

yes

schema-free

Typing

predefined data types such as float or date

yes

JSON types

yes

integer and binary

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

with tags

SQL

Support of SQL

SQL-like DML and DDL statements

yes

but not compliant to any SQL standard

SQL-like query language

APIs and other access methods

JDBC
ODBC
Thrift

RESTful HTTP/JSON API

ADO.NET
DAO
ODBC
OLE DB

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

HTTP API

Supported programming languages

C++
Java
PHP
Python

C#
Java
JavaScript
Objective-C
PHP
Ruby

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

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

Server-side scripts

Stored procedures

yes

user defined functions and integration of map-reduce

View functions (Map-Reduce) in JavaScript

yes

since Access 2010 using the ACE-engine

JavaScript

Triggers

yes

since Access 2010 using the ACE-engine

JavaScript

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

Sharding

Implicit feature of the cloud service

Sharding

consistent hashing

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor

Multi-source replication
Source-replica replication

none

yes

Implicit feature of the cloud service

Source-replica replication with selectable replication factor

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

query execution via MapReduce

yes

with Hadoop integration

Integration with Hadoop/HDInsight on Azure*

with Hadoop integration

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency

Bounded Staleness
Consistent Prefix
Eventual Consistency
Immediate Consistency

Consistency level configurable on request level
Session Consistency

Immediate Consistency

Foreign keys

Referential integrity

yes

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

Multi-item ACID transactions with snapshot isolation within a partition

ACID

Concurrency

Support for concurrent manipulation of data

yes

Optimistic locking

yes

Durability

Support for making data persistent

yes

but no files for transaction logging

yes

by using LevelDB

In-memory capabilities

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

yes

Transient mode

User concepts

Access control

Access rights for users, groups and roles

Access rights for users can be defined per database

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

Access rights can be defined down to the item level

Cryptographically strong user authentication and audit trail

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