DBMS > Firebase Realtime Database vs. HBase vs. Microsoft Access vs. Microsoft Azure Cosmos DB

System Properties Comparison Firebase Realtime Database vs. HBase vs. Microsoft Access vs. Microsoft Azure Cosmos DB

Please select another system to include it in the comparison.

Editorial information provided by DB-Engines

Name

Description

Cloud-hosted realtime document store. iOS, Android, and JavaScript clients share one Realtime Database instance and automatically receive updates with the newest data.

Wide-column store based on Apache Hadoop and on concepts of BigTable

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

Primary database model

Document store

Wide column store

Relational DBMS

Document store
Graph DBMS
Key-value store
Wide column store

Secondary database models

Spatial DBMS

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

Score	14.29
Rank	#39	Overall
	#6	Document stores

Score	30.50
Rank	#26	Overall
	#2	Wide column stores

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

Website

firebase.google.com/products/realtime-database

hbase.apache.org

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

azure.microsoft.com/services/cosmos-db

Technical documentation

firebase.google.com/docs/database

hbase.apache.org/book.html

developer.microsoft.com/en-us/access

learn.microsoft.com/azure/cosmos-db

Developer

Google

acquired by Google 2014

Apache Software Foundation

Apache top-level project, originally developed by Powerset

Microsoft

Initial release

2012

2008

1992

2014

Current release

2.3.4, January 2021

1902 (16.0.11328.20222), March 2019

License

Commercial or Open Source

commercial

Open Source

Apache version 2

commercial

Bundled with Microsoft Office

commercial

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

C++

Server operating systems

hosted

Linux
Unix
Windows

using Cygwin

Windows

Not a real database server, but making use of DLLs

hosted

Data scheme

schema-free

schema-free, schema definition possible

yes

schema-free

Typing

predefined data types such as float or date

yes

options to bring your own types, AVRO

yes

JSON types

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

SQL

Support of SQL

yes

but not compliant to any SQL standard

SQL-like query language

APIs and other access methods

Android
iOS
JavaScript API
RESTful HTTP API

Java API
RESTful HTTP API
Thrift

ADO.NET
DAO
ODBC
OLE DB

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

Supported programming languages

Java
JavaScript
Objective-C

C
C#
C++
Groovy
Java
PHP
Python
Scala

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

Server-side scripts

Stored procedures

limited functionality with using 'rules'

yes

Coprocessors in Java

yes

since Access 2010 using the ACE-engine

JavaScript

Triggers

Callbacks are triggered when data changes

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

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication
Source-replica replication

none

yes

Implicit feature of the cloud service

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

with Hadoop integration

Integration with Hadoop/HDInsight on Azure*

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency

if the client is offline
Immediate Consistency

if the client is online

Immediate Consistency or Eventual Consistency

Bounded Staleness
Consistent Prefix
Eventual Consistency
Immediate Consistency

Consistency level configurable on request level
Session Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

yes

Single row ACID (across millions of columns)

ACID

but no files for transaction logging

Multi-item ACID transactions with snapshot isolation within a partition

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

yes, based on authentication and database rules

Access Control Lists (ACL) for RBAC, integration with Apache Ranger for RBAC & ABAC

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

Access rights can be defined down to the item level

More information provided by the system vendor

We invite representatives of system vendors to contact us for updating and extending the system information,
and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.