DBMS > Amazon DocumentDB vs. DuckDB vs. Lovefield

System Properties Comparison Amazon DocumentDB vs. DuckDB vs. Lovefield

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Editorial information provided by DB-Engines

Name

Description

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

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

Embeddable relational database for web apps written in pure JavaScript

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	4.57
Rank	#74	Overall
	#40	Relational DBMS

Score	0.29
Rank	#293	Overall
	#133	Relational DBMS

Website

aws.amazon.com/documentdb

duckdb.org

google.github.io/lovefield

Technical documentation

aws.amazon.com/documentdb/resources

duckdb.org/docs

github.com/google/lovefield/blob/master/docs/spec_index.md

Developer

Google

Initial release

2019

2018

2014

Current release

0.10, February 2024

2.1.12, February 2017

License

Commercial or Open Source

commercial

Open Source

MIT License

Open Source

Apache 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++

JavaScript

Server operating systems

hosted

server-less

server-less, requires a JavaScript environment (browser, Node.js)

tested with Chrome, Firefox, IE, Safari

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 query language

via JavaScript builder pattern

APIs and other access methods

proprietary protocol using JSON (MongoDB compatible)

Arrow Database Connectivity (ADBC)
CLI Client
JDBC
ODBC

Supported programming languages

Go
Java
JavaScript (Node.js)
PHP
Python

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

JavaScript

Server-side scripts

Stored procedures

Triggers

Using read-only observers

Partitioning methods

Methods for storing different data on different nodes

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

yes

Transaction concepts

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

Atomic single-document operations

ACID

Concurrency

Support for concurrent manipulation of data

yes

yes, multi-version concurrency control (MVCC)

yes

Durability

Support for making data persistent

yes

yes, by using IndexedDB or the cloud service Firebase Realtime Database

In-memory capabilities

Is there an option to define some or all structures to be held in-memory only.

yes

using MemoryDB

User concepts

Access control

Access rights for users and roles

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More resources

Recent citations in the news

My First Billion (of Rows) in DuckDB | by João Pedro | May, 2024
1 May 2024, Towards Data Science

Enabling Remote Query Execution through DuckDB Extensions
12 March 2024, InfoQ.com

DuckDB Walks to the Beat of Its Own Analytics Drum
5 March 2024, Datanami

MotherDuck Raises $52.5 Million Series B Funding as DuckDB Adoption Soars
20 September 2023, PR Newswire

Seattle startup MotherDuck raises $52.5M at a $400M valuation to fuel DuckDB analytics platform
20 September 2023, GeekWire

provided by Google News

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