DBMS > DuckDB vs. Fauna vs. Google Cloud Spanner

System Properties Comparison DuckDB vs. Fauna vs. Google Cloud Spanner

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Editorial information provided by DB-Engines

Name

Description

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

Fauna provides a web-native interface, with support for GraphQL and custom business logic that integrates seamlessly with the rest of the serverless ecosystem. The underlying globally distributed storage and compute platform is fast, consistent, and reliable, with a modern security infrastructure.

A horizontally scalable, globally consistent, relational database service. It is the externalization of the core Google database that runs the biggest aspects of Google, like Ads and Google Play.

Primary database model

Relational DBMS

Document store
Graph DBMS
Relational DBMS
Time Series DBMS

Relational DBMS

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

Score	4.68
Rank	#76	Overall
	#41	Relational DBMS

Score	1.55
Rank	#154	Overall
	#26	Document stores
	#14	Graph DBMS
	#72	Relational DBMS
	#13	Time Series DBMS

Score	2.89
Rank	#105	Overall
	#53	Relational DBMS

Website

duckdb.org

fauna.com

cloud.google.com/spanner

Technical documentation

duckdb.org/docs

docs.fauna.com

cloud.google.com/spanner/docs

Developer

Fauna, Inc.

Google

Initial release

2018

2014

2017

Current release

0.10, February 2024

License

Commercial or Open Source

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

C++

Scala

Server operating systems

server-less

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

Query statements complying to ANSI 2011

APIs and other access methods

Arrow Database Connectivity (ADBC)
CLI Client
JDBC
ODBC

RESTful HTTP API

gRPC (using protocol buffers) API
JDBC

At present, JDBC supports read-only queries. No support for DDL or DML statements.
RESTful HTTP API

Supported programming languages

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

C#
Go
Java
JavaScript
Python
Ruby
Scala
Swift

Go
Java
JavaScript (Node.js)
Python

Server-side scripts

Stored procedures

user defined functions

Triggers

Partitioning methods

Methods for storing different data on different nodes

none

horizontal partitioning

consistent hashing

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

none

Multi-source replication

Multi-source replication with 3 replicas for regional instances.

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

using Google Cloud Dataflow

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Foreign keys

Referential integrity

yes

by using interleaved tables, this features focuses more on performance improvements than on referential integrity

Transaction concepts

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

ACID

Strict serializable isolation

Concurrency

Support for concurrent manipulation of data

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

Identity management, authentication, and access control

Access rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)

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More resources

Recent citations in the news

This Alternative to Pandas Processes Data 350 Times Faster
29 April 2024, Medium

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

How to read OSM data with DuckDB | Kamil Raczycki
1 March 2024, Towards Data Science

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

provided by Google News

Slicing the Gordian Knot: A leap to real-time systems of truth
3 February 2024, SiliconANGLE News

Fauna Launches Distributed Document-Relational Database On Google Cloud Marketplace
21 March 2024, GlobeNewswire

Fauna Adds Transformative Schema-as-Code Capabilities to Enterprise Proven, Document-Relational Database
15 November 2023, Business Wire

Fauna Query Language tamed to appeal to developers
22 August 2023, The Register

Utah Natural Heritage Program
17 October 2023, Utah Division of Wildlife Resources

provided by Google News

Google Improves Cloud Spanner: More Compute and Storage without Price Increase
14 October 2023, InfoQ.com

Google turns up the heat on AWS, claims Cloud Spanner is half the cost of DynamoDB
11 October 2023, TechCrunch

Google makes its Cloud Spanner database service faster and more cost-efficient
11 October 2023, SiliconANGLE News

Google Spanner: When Do You Need to Move to It?
11 September 2023, hackernoon.com

Google Cloud Spanner competes directly with Amazon DynamoDB
12 October 2023, Techzine Europe

provided by Google News

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