DBMS > Apache Doris vs. EsgynDB vs. Firebase Realtime Database vs. Google BigQuery

System Properties Comparison Apache Doris vs. EsgynDB vs. Firebase Realtime Database vs. Google BigQuery

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Editorial information provided by DB-Engines

Name

Description

An MPP-based analytics DBMS embracing the MySQL protocol

Enterprise-class SQL-on-Hadoop solution, powered by Apache Trafodion

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

Primary database model

Relational DBMS

Document store

Relational DBMS

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

Score	0.60
Rank	#247	Overall
	#113	Relational DBMS

Score	0.25
Rank	#312	Overall
	#138	Relational DBMS

Score	13.64
Rank	#39	Overall
	#6	Document stores

Score	58.10
Rank	#19	Overall
	#13	Relational DBMS

Website

doris.apache.org
github.com/apache/doris

www.esgyn.cn

firebase.google.com/products/realtime-database

cloud.google.com/bigquery

Technical documentation

github.com/apache/doris/wiki

firebase.google.com/docs/database

cloud.google.com/bigquery/docs

Developer

Apache Software Foundation, originally contributed from Baidu

Esgyn

Google

acquired by Google 2014

Google

Initial release

2017

2015

2012

2010

Current release

1.2.2, February 2023

License

Commercial or Open Source

Open Source

Apache Version 2.0

commercial

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++, Java

Server operating systems

Linux

hosted

Data scheme

yes

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

JDBC
MySQL client

ADO.NET
JDBC
ODBC

Android
iOS
JavaScript API
RESTful HTTP API

RESTful HTTP/JSON API

Supported programming languages

Java

All languages supporting JDBC/ODBC/ADO.Net

Java
JavaScript
Objective-C

.Net
Java
JavaScript
Objective-C
PHP
Python
Ruby

Server-side scripts

Stored procedures

user defined functions

Java Stored Procedures

limited functionality with using 'rules'

user defined functions

in JavaScript

Triggers

Callbacks are triggered when data changes

Partitioning methods

Methods for storing different data on different nodes

horizontal partitioning

Sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

none

Multi-source replication between multi datacenters

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

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

ACID

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

fine grained access rights according to SQL-standard

yes, based on authentication and database rules

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

Google Cloud Identity & Access Management (IAM)

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