DBMS > Amazon DocumentDB vs. Apache Doris vs. DuckDB vs. Google BigQuery

System Properties Comparison Amazon DocumentDB vs. Apache Doris vs. DuckDB vs. Google BigQuery

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Editorial information provided by DB-Engines

Name

Description

Fast, scalable, highly available, and fully managed MongoDB-compatible database service

An MPP-based analytics DBMS embracing the MySQL protocol

An embeddable, in-process, column-oriented SQL OLAP RDBMS

Large scale data warehouse service with append-only tables

Primary database model

Document store

Relational DBMS

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

Score	1.91
Rank	#132	Overall
	#24	Document stores

Score	0.57
Rank	#244	Overall
	#113	Relational DBMS

Score	4.57
Rank	#74	Overall
	#40	Relational DBMS

Score	60.38
Rank	#19	Overall
	#13	Relational DBMS

Website

aws.amazon.com/documentdb

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

duckdb.org

cloud.google.com/bigquery

Technical documentation

aws.amazon.com/documentdb/resources

github.com/apache/doris/wiki

duckdb.org/docs

cloud.google.com/bigquery/docs

Developer

Apache Software Foundation, originally contributed from Baidu

Google

Initial release

2019

2017

2018

2010

Current release

1.2.2, February 2023

0.10, February 2024

License

Commercial or Open Source

commercial

Open Source

Apache Version 2.0

Open Source

MIT License

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.

Implementation language

Java

C++

Server operating systems

hosted

Linux

server-less

hosted

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

proprietary protocol using JSON (MongoDB compatible)

JDBC
MySQL client

Arrow Database Connectivity (ADBC)
CLI Client
JDBC
ODBC

RESTful HTTP/JSON API

Supported programming languages

Go
Java
JavaScript (Node.js)
PHP
Python

Java

C
C#

3rd party driver
C++
Crystal

3rd party driver
Go

3rd party driver
Java
Lisp

3rd party driver
Python
R
Ruby

3rd party driver
Rust
Swift
Zig

3rd party driver

.Net
Java
JavaScript
Objective-C
PHP
Python
Ruby

Server-side scripts

Stored procedures

user defined functions

in JavaScript

Triggers

Partitioning methods

Methods for storing different data on different nodes

none

horizontal partitioning

none

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-availability zones for high availability, asynchronous replication for up to 15 read replicas

none

MapReduce

Offers an API for user-defined Map/Reduce methods

may be implemented via Amazon Elastic MapReduce (Amazon EMR)

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Foreign keys

Referential integrity

typically not used, however similar functionality with DBRef possible

Transaction concepts

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

Atomic single-document operations

ACID

Since BigQuery is designed for querying data

Concurrency

Support for concurrent manipulation of data

yes

yes, multi-version concurrency control (MVCC)

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

Access rights for users and roles

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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