DBMS > FeatureBase vs. Firebase Realtime Database vs. IBM Db2 warehouse vs. Snowflake

System Properties Comparison FeatureBase vs. Firebase Realtime Database vs. IBM Db2 warehouse vs. Snowflake

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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.

Cloud-based data warehousing service

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

Primary database model

Relational DBMS

Document store

Relational DBMS

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

Score	0.23
Rank	#296	Overall
	#134	Relational DBMS

Score	13.60
Rank	#39	Overall
	#6	Document stores

Score	1.26
Rank	#162	Overall
	#73	Relational DBMS

Score	133.72
Rank	#7	Overall
	#5	Relational DBMS

Website

www.featurebase.com

firebase.google.com/products/realtime-database

www.ibm.com/products/db2/warehouse

www.snowflake.com

Technical documentation

docs.featurebase.com

firebase.google.com/docs/database

docs.snowflake.net/manuals/index.html

Developer

Molecula and Pilosa Open Source Contributors

Google

acquired by Google 2014

IBM

Snowflake Computing Inc.

Initial release

2017

2012

2014

Current release

2022, May 2022

License

Commercial or Open Source

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

Server operating systems

Linux
macOS

hosted

Data scheme

yes

schema-free

yes

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

Typing

predefined data types such as float or date

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.

Import/export of XML data possible

yes

Secondary indexes

yes

SQL

Support of SQL

SQL queries

yes

APIs and other access methods

gRPC
JDBC
Kafka Connector
ODBC

Android
iOS
JavaScript API
RESTful HTTP API

.NET Client API
JDBC
ODBC
OLE DB

CLI Client
JDBC
ODBC

Supported programming languages

Java
Python

Java
JavaScript
Objective-C

Java
JavaScript (Node.js)
Perl
PHP
Python
R
Ruby

JavaScript (Node.js)
Python

Server-side scripts

Stored procedures

limited functionality with using 'rules'

PL/SQL, SQL PL

user defined functions

Triggers

Callbacks are triggered when data changes

yes

similar concept for controling cloud resources

Partitioning methods

Methods for storing different data on different nodes

Sharding

yes

Replication methods

Methods for redundantly storing data on multiple nodes

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

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

Foreign keys

Referential integrity

yes

Transaction concepts

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

yes

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes, using Linux fsync

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

fine grained access rights according to SQL-standard

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

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