DBMS > Badger vs. Firebase Realtime Database vs. Google BigQuery vs. StarRocks

System Properties Comparison Badger vs. Firebase Realtime Database vs. Google BigQuery vs. StarRocks

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Editorial information provided by DB-Engines

Name

Description

An embeddable, persistent, simple and fast Key-Value Store, written purely in Go.

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

An open source, high-performance columnar analytical database that enables real-time, multi-dimensional, and highly concurrent data analytics

Forked from Apache Doris

Primary database model

Key-value store

Document store

Relational DBMS

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

Score	0.22
Rank	#320	Overall
	#47	Key-value stores

Score	13.64
Rank	#39	Overall
	#6	Document stores

Score	58.10
Rank	#19	Overall
	#13	Relational DBMS

Score	0.93
Rank	#198	Overall
	#93	Relational DBMS

Website

github.com/dgraph-io/badger

firebase.google.com/products/realtime-database

cloud.google.com/bigquery

www.starrocks.io

Technical documentation

godoc.org/github.com/dgraph-io/badger

firebase.google.com/docs/database

cloud.google.com/bigquery/docs

docs.starrocks.io/en-us/latest/introduction/StarRocks_intro

Developer

DGraph Labs

Google

acquired by Google 2014

Google

The Linux Foundation

since Feb 2023

Initial release

2017

2012

2010

2020

Current release

2.5.3, March 2023

License

Commercial or Open Source

Open Source

Apache 2.0

commercial

Open Source

Apache Version 2.0

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

C++, Java

Server operating systems

BSD
Linux
OS X
Solaris
Windows

hosted

Linux

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

APIs and other access methods

Android
iOS
JavaScript API
RESTful HTTP API

RESTful HTTP/JSON API

JDBC
MySQL protocol

Supported programming languages

Java
JavaScript
Objective-C

.Net
Java
JavaScript
Objective-C
PHP
Python
Ruby

Java

Server-side scripts

Stored procedures

limited functionality with using 'rules'

user defined functions

in JavaScript

user defined functions

Triggers

Callbacks are triggered when data changes

Partitioning methods

Methods for storing different data on different nodes

none

horizontal partitioning (by range and hash)

Replication methods

Methods for redundantly storing data on multiple nodes

none

MapReduce

Offers an API for user-defined Map/Reduce methods

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

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)

Role based access control and fine grained access rights

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