DBMS > FatDB vs. Google Cloud Firestore vs. Immudb vs. Ingres vs. Trafodion

System Properties Comparison FatDB vs. Google Cloud Firestore vs. Immudb vs. Ingres vs. Trafodion

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.

Apache Trafodion has been retired in 2021. Therefore it is excluded from the DB-Engines Ranking.

Description

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.

An open source immutable (append-only) database with cryptographic verification which makes it tamper-resistant and fully auditable.

Well established RDBMS

Transactional SQL-on-Hadoop DBMS

Primary database model

Document store
Key-value store

Document store

Key-value store

Relational DBMS

Secondary database models

Relational DBMS

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

Score	7.85
Rank	#51	Overall
	#8	Document stores

Score	0.24
Rank	#305	Overall
	#43	Key-value stores

Score	4.11
Rank	#81	Overall
	#44	Relational DBMS

Website

firebase.google.com/products/firestore

github.com/codenotary/immudb
immudb.io

www.actian.com/databases/ingres

trafodion.apache.org

Technical documentation

firebase.google.com/docs/firestore

docs.immudb.io

docs.actian.com/ingres

trafodion.apache.org/documentation.html

Developer

FatCloud

Google

Codenotary

Actian Corporation

Apache Software Foundation, originally developed by HP

Initial release

2012

2017

2020

1974

originally developed at University Berkely in early 1970s

2014

Current release

1.2.3, April 2022

11.2, May 2022

2.3.0, February 2019

License

Commercial or Open Source

commercial

Open Source

Apache Version 2.0

commercial

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++, Java

Server operating systems

Windows

hosted

BSD
Linux
macOS
Solaris
Windows
z/OS

AIX
HP Open VMS
HP-UX
Linux
Solaris
Windows

Linux

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.

but tools for importing/exporting data from/to XML-files available

Secondary indexes

yes

SQL

Support of SQL

Via inetgration in SQL Server

SQL-like syntax

yes

APIs and other access methods

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

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

gRPC protocol
PostgreSQL wire protocol

.NET Client API
JDBC
ODBC
proprietary protocol (OpenAPI)

ADO.NET
JDBC
ODBC

Supported programming languages

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

.Net
Go
Java
JavaScript (Node.js)
Python

All languages supporting JDBC/ODBC/ADO.Net

Server-side scripts

Stored procedures

yes

via applications

yes, Firebase Rules & Cloud Functions

yes

Java Stored Procedures

Triggers

yes

via applications

yes, with Cloud Functions

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

horizontal partitioning

Ingres Star to access multiple databases simultaneously

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor

Multi-source replication

Ingres Replicator

yes, via HBase

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Using Cloud Dataflow

yes

via user defined functions and HBase

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency
Immediate Consistency

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

yes

ACID

Concurrency

Support for concurrent manipulation of data

yes

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.

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

More information provided by the system vendor

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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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