DBMS > FeatureBase vs. Firebase Realtime Database vs. Microsoft Azure Cosmos DB vs. OrigoDB

System Properties Comparison FeatureBase vs. Firebase Realtime Database vs. Microsoft Azure Cosmos DB vs. OrigoDB

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Editorial information provided by DB-Engines

Name

Description

Real-time database platform that powers real-time analytics and machine learning applications by simultaneously executing low-latency, high-throughput, and highly concurrent workloads.

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

Globally distributed, horizontally scalable, multi-model database service

A fully ACID in-memory object graph database

Primary database model

Relational DBMS

Document store

Document store
Graph DBMS
Key-value store
Wide column store

Document store
Object oriented DBMS

Secondary database models

Spatial DBMS

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

Score	0.22
Rank	#309	Overall
	#139	Relational DBMS

Score	14.29
Rank	#39	Overall
	#6	Document stores

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

Score	0.00
Rank	#383	Overall
	#53	Document stores
	#20	Object oriented DBMS

Website

www.featurebase.com

firebase.google.com/products/realtime-database

azure.microsoft.com/services/cosmos-db

origodb.com

Technical documentation

docs.featurebase.com

firebase.google.com/docs/database

learn.microsoft.com/azure/cosmos-db

origodb.com/docs

Developer

Molecula and Pilosa Open Source Contributors

Google

acquired by Google 2014

Microsoft

Robert Friberg et al

Initial release

2017

2012

2014

2009

under the name LiveDB

Current release

2022, May 2022

License

Commercial or Open Source

commercial

Open Source

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

Server operating systems

Linux
macOS

hosted

Linux
Windows

Data scheme

yes

schema-free

yes

Typing

predefined data types such as float or date

yes

JSON types

User defined using .NET types and collections

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.

can be achieved using .NET

Secondary indexes

yes

All properties auto-indexed by default

yes

SQL

Support of SQL

SQL queries

SQL-like query language

APIs and other access methods

gRPC
JDBC
Kafka Connector
ODBC

Android
iOS
JavaScript API
RESTful HTTP API

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

.NET Client API
HTTP API
LINQ

Supported programming languages

Java
Python

Java
JavaScript
Objective-C

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

.Net

Server-side scripts

Stored procedures

limited functionality with using 'rules'

JavaScript

yes

Triggers

Callbacks are triggered when data changes

JavaScript

yes

Domain Events

Partitioning methods

Methods for storing different data on different nodes

Sharding

Implicit feature of the cloud service

horizontal partitioning

client side managed; servers are not synchronized

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Implicit feature of the cloud service

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

Eventual Consistency

if the client is offline
Immediate Consistency

if the client is online

Bounded Staleness
Consistent Prefix
Eventual Consistency
Immediate Consistency

Consistency level configurable on request level
Session Consistency

Foreign keys

Referential integrity

yes

depending on model

Transaction concepts

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

yes

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, using Linux fsync

yes

Write ahead log

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 rights can be defined down to the item level

Role based authorization

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