DBMS > DuckDB vs. FatDB vs. Google Cloud Firestore vs. H2 vs. Yaacomo

System Properties Comparison DuckDB vs. FatDB vs. Google Cloud Firestore vs. H2 vs. Yaacomo

Editorial information provided by DB-Engines

Name

FatDB/FatCloud has ceased operations as a company with February 2014. FatDB is discontinued and excluded from the ranking.

Yaacomo seems to be discontinued and is removed from the DB-Engines ranking

Description

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

A .NET NoSQL DBMS that can integrate with and extend SQL Server.

Cloud Firestore is an auto-scaling document database for storing, syncing, and querying data for mobile and web apps. It offers seamless integration with other Firebase and Google Cloud Platform products.

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

OpenCL based in-memory RDBMS, designed for efficiently utilizing the hardware via parallel computing

Primary database model

Relational DBMS

Document store
Key-value store

Document store

Relational DBMS

Secondary database models

Spatial DBMS

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

Score	4.63
Rank	#69	Overall
	#37	Relational DBMS

Score	7.36
Rank	#53	Overall
	#9	Document stores

Score	8.33
Rank	#46	Overall
	#30	Relational DBMS

Website

duckdb.org

firebase.google.com/products/firestore

www.h2database.com

yaacomo.com

Technical documentation

duckdb.org/docs

firebase.google.com/docs/firestore

www.h2database.com/html/main.html

Developer

FatCloud

Google

Thomas Mueller

Q2WEB GmbH

Initial release

2018

2012

2017

2005

2009

Current release

1.0.0, June 2024

2.2.220, July 2023

License

Commercial or Open Source

Open Source

MIT License

commercial

Open Source

dual-licence (Mozilla public license, Eclipse public 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++

Java

Server operating systems

server-less

Windows

hosted

All OS with a Java VM

Android
Linux
Windows

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

Via inetgration in SQL Server

yes

APIs and other access methods

Arrow Database Connectivity (ADBC)
CLI Client
JDBC
ODBC

.NET Client API
LINQ
RESTful HTTP API
RPC
Windows WCF Bindings

Android
gRPC (using protocol buffers) API
iOS
JavaScript API
RESTful HTTP API

JDBC
ODBC

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

Go
Java
JavaScript
JavaScript (Node.js)
Objective-C
Python

Java

Server-side scripts

Stored procedures

yes

via applications

yes, Firebase Rules & Cloud Functions

Java Stored Procedures and User-Defined Functions

Triggers

yes

via applications

yes, with Cloud Functions

yes

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

none

horizontal partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

none

selectable replication factor

Multi-source replication

With clustering: 2 database servers on different computers operate on identical copies of a database

Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Using Cloud Dataflow

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency
Immediate Consistency

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

yes

ACID

Concurrency

Support for concurrent manipulation of data

yes, multi-version concurrency control (MVCC)

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

Can implement custom security layer via applications

Access rights for users, groups and roles based on Google Cloud Identity and Access Management. Security Rules for 3rd party authentication using Firebase Auth.

fine grained access rights according to SQL-standard

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More resources

DB-Engines blog posts

Cloud-based DBMS's popularity grows at high rates
12 December 2019, Paul Andlinger

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DuckDB: In-Process Python Analytics for Not-Quite-Big Data
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Google's Cloud Firestore is now generally available
31 January 2019, ZDNet

Google launches Cloud Firestore, a new document database for app developers
3 October 2017, TechCrunch

provided by Google News

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