DBMS > Firebase Realtime Database vs. Google BigQuery vs. Hive vs. ReductStore

System Properties Comparison Firebase Realtime Database vs. Google BigQuery vs. Hive vs. ReductStore

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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.

Large scale data warehouse service with append-only tables

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

Designed to manage unstructured time-series data efficiently, providing unique features such as storing time-stamped blobs with labels, customizable data retention policies, and a straightforward FIFO quota system.

Primary database model

Document store

Relational DBMS

Time Series DBMS

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

Score	13.64
Rank	#39	Overall
	#6	Document stores

Score	58.10
Rank	#19	Overall
	#13	Relational DBMS

Score	59.76
Rank	#18	Overall
	#12	Relational DBMS

Score	0.05
Rank	#384	Overall
	#44	Time Series DBMS

Website

firebase.google.com/products/realtime-database

cloud.google.com/bigquery

hive.apache.org

github.com/reductstore
www.reduct.store

Technical documentation

firebase.google.com/docs/database

cloud.google.com/bigquery/docs

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

www.reduct.store/docs

Developer

Google

acquired by Google 2014

Google

Apache Software Foundation

initially developed by Facebook

ReductStore LLC

Initial release

2012

2010

2012

2023

Current release

3.1.3, April 2022

1.9, March 2024

License

Commercial or Open Source

commercial

Open Source

Apache Version 2

Open Source

Business Source License 1.1

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

Java

C++, Rust

Server operating systems

hosted

All OS with a Java VM

Docker
Linux
macOS
Windows

Data scheme

schema-free

yes

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.

Secondary indexes

yes

SQL

Support of SQL

yes

SQL-like DML and DDL statements

APIs and other access methods

Android
iOS
JavaScript API
RESTful HTTP API

RESTful HTTP/JSON API

JDBC
ODBC
Thrift

HTTP API

Supported programming languages

Java
JavaScript
Objective-C

.Net
Java
JavaScript
Objective-C
PHP
Python
Ruby

C++
Java
PHP
Python

C++
JavaScript (Node.js)
Python
Rust

Server-side scripts

Stored procedures

limited functionality with using 'rules'

user defined functions

in JavaScript

yes

user defined functions and integration of map-reduce

Triggers

Callbacks are triggered when data changes

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

query execution via MapReduce

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

Eventual Consistency

Foreign keys

Referential integrity

Transaction concepts

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

yes

Since BigQuery is designed for querying data

Concurrency

Support for concurrent manipulation of data

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.

User concepts

Access control

yes, based on authentication and database rules

Access privileges (owner, writer, reader) on dataset, table or view level

Google Cloud Identity & Access Management (IAM)

Access rights for users, groups and roles

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