DBMS > Apache Doris vs. Derby vs. Google BigQuery

System Properties Comparison Apache Doris vs. Derby vs. Google BigQuery

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Editorial information provided by DB-Engines

Name

Description

An MPP-based analytics DBMS embracing the MySQL protocol

Full-featured RDBMS with a small footprint, either embedded into a Java application or used as a database server.

Large scale data warehouse service with append-only tables

Primary database model

Relational DBMS

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

Score	0.68
Rank	#246	Overall
	#114	Relational DBMS

Score	6.07
Rank	#71	Overall
	#39	Relational DBMS

Score	53.44
Rank	#21	Overall
	#14	Relational DBMS

Website

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

db.apache.org/derby

cloud.google.com/bigquery

Technical documentation

github.com/apache/doris/wiki

db.apache.org/derby/manuals/index.html

cloud.google.com/bigquery/docs

Developer

Apache Software Foundation, originally contributed from Baidu

Apache Software Foundation

Google

Initial release

2017

1997

2010

Current release

1.2.2, February 2023

10.16.1.1, May 2022

License

Commercial or Open Source

Open Source

Apache Version 2.0

Open Source

Apache version 2

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

Server operating systems

Linux

All OS with a Java VM

hosted

Data scheme

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.

yes

Secondary indexes

yes

SQL

Support of SQL

yes

APIs and other access methods

JDBC
MySQL client

JDBC

RESTful HTTP/JSON API

Supported programming languages

Java

.Net
Java
JavaScript
Objective-C
PHP
Python
Ruby

Server-side scripts

Stored procedures

user defined functions

Java Stored Procedures

user defined functions

in JavaScript

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

horizontal partitioning

none

Replication methods

Methods for redundantly storing data on multiple nodes

none

Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

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.

yes

User concepts

Access control

fine grained access rights according to SQL-standard

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

Google Cloud Identity & Access Management (IAM)

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