DBMS > BigObject vs. Firebase Realtime Database vs. Netezza vs. Snowflake

System Properties Comparison BigObject vs. Firebase Realtime Database vs. Netezza vs. Snowflake

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Editorial information provided by DB-Engines

Name

Description

Analytic DBMS for real-time computations and queries

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

Data warehouse and analytics appliance part of IBM PureSystems

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

Primary database model

Relational DBMS

a hierachical model (tree) can be imposed

Document store

Relational DBMS

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

Score	0.13
Rank	#342	Overall
	#150	Relational DBMS

Score	15.00
Rank	#39	Overall
	#6	Document stores

Score	10.18
Rank	#46	Overall
	#29	Relational DBMS

Score	123.20
Rank	#9	Overall
	#6	Relational DBMS

Website

bigobject.io

firebase.google.com/products/realtime-database

www.ibm.com/products/netezza

www.snowflake.com

Technical documentation

docs.bigobject.io

firebase.google.com/docs/database

docs.snowflake.net/manuals/index.html

Developer

BigObject, Inc.

Google

acquired by Google 2014

IBM

Snowflake Computing Inc.

Initial release

2015

2012

2000

2014

License

Commercial or Open Source

commercial

free community edition available

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.

Server operating systems

Linux

distributed as a docker-image
OS X

distributed as a docker-image (boot2docker)
Windows

distributed as a docker-image (boot2docker)

hosted

Linux

included in appliance

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.

yes

Secondary indexes

yes

SQL

Support of SQL

SQL-like DML and DDL statements

yes

APIs and other access methods

fluentd
ODBC
RESTful HTTP API

Android
iOS
JavaScript API
RESTful HTTP API

JDBC
ODBC
OLE DB

CLI Client
JDBC
ODBC

Supported programming languages

Java
JavaScript
Objective-C

C
C++
Fortran
Java
Lua
Perl
Python
R

JavaScript (Node.js)
Python

Server-side scripts

Stored procedures

Lua

limited functionality with using 'rules'

yes

user defined functions

Triggers

Callbacks are triggered when data changes

similar concept for controling cloud resources

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

yes

Replication methods

Methods for redundantly storing data on multiple nodes

none

Source-replica replication

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

none

Eventual Consistency

if the client is offline
Immediate Consistency

if the client is online

Immediate Consistency

Foreign keys

Referential integrity

yes

automatically between fact table and dimension tables

yes

Transaction concepts

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

yes

ACID

Concurrency

Support for concurrent manipulation of data

yes

Read/write lock on objects (tables, trees)

yes

Durability

Support for making data persistent

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

Users with fine-grained authorization concept

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

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