DBMS > Google Cloud Firestore vs. JaguarDB vs. Oracle NoSQL vs. Sadas Engine

System Properties Comparison Google Cloud Firestore vs. JaguarDB vs. Oracle NoSQL vs. Sadas Engine

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Editorial information provided by DB-Engines

Name

Description

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.

Performant, highly scalable DBMS for AI and IoT applications

A multi-model, scalable, distributed NoSQL database, designed to provide highly reliable, flexible, and available data management across a configurable set of storage nodes

SADAS Engine is a columnar DBMS specifically designed for high performance in data warehouse environments

Primary database model

Document store

Key-value store
Vector DBMS

Document store
Key-value store
Relational DBMS

Relational DBMS

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

Score	6.63
Rank	#54	Overall
	#9	Document stores

Score	0.00
Rank	#385	Overall
	#61	Key-value stores
	#16	Vector DBMS

Score	3.07
Rank	#86	Overall
	#15	Document stores
	#11	Key-value stores
	#47	Relational DBMS

Score	0.00
Rank	#385	Overall
	#159	Relational DBMS

Website

firebase.google.com/products/firestore

www.jaguardb.com

www.oracle.com/database/nosql/technologies/nosql

www.sadasengine.com

Technical documentation

firebase.google.com/docs/firestore

www.jaguardb.com/support.html

docs.oracle.com/en/database/other-databases/nosql-database/index.html

www.sadasengine.com/en/sadas-engine-download-free-trial-and-documentation/#documentation

Developer

Google

DataJaguar, Inc.

Oracle

SADAS s.r.l.

Initial release

2017

2015

2011

2006

Current release

3.3 July 2023

24.1, May 2024

8.0

License

Commercial or Open Source

commercial

Open Source

GPL V3.0

Open Source

Proprietary for Enterprise Edition (Oracle Database EE license has Oracle NoSQL database EE covered: details)

commercial

free trial version available

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++

the server part. Clients available in other languages

Java

C++

Server operating systems

hosted

Linux

Linux
Solaris SPARC/x86

AIX
Linux
Windows

Data scheme

schema-free

yes

Support Fixed schema and Schema-less deployment with the ability to interoperate between them.

yes

Typing

predefined data types such as float or date

yes

optional

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

A subset of ANSI SQL is implemented

but no views, foreign keys, triggers

SQL-like DML and DDL statements

yes

APIs and other access methods

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

JDBC
ODBC

RESTful HTTP API

JDBC
ODBC
Proprietary protocol

Supported programming languages

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

C
C++
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
Scala

C
C#
Go
Java
JavaScript (Node.js)
Python

.Net
C
C#
C++
Groovy
Java
PHP
Python

Server-side scripts

Stored procedures

yes, Firebase Rules & Cloud Functions

Triggers

yes, with Cloud Functions

Partitioning methods

Methods for storing different data on different nodes

Sharding

horizontal partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication

Electable source-replica replication per shard. Support distributed global deployment with Multi-region table feature

none

MapReduce

Offers an API for user-defined Map/Reduce methods

Using Cloud Dataflow

with Hadoop integration

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency

Eventual Consistency
Immediate Consistency

depending on configuration

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

yes

configurable

ACID within a storage node (=shard)

Concurrency

Support for concurrent manipulation of data

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

off heap cache

yes

managed by 'Learn by Usage'

User concepts

Access control

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

rights management via user accounts

Access rights for users and roles

Access rights for users, groups and roles according to SQL-standard

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More resources

DB-Engines blog posts

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