DBMS > Databricks vs. Google Cloud Firestore vs. Sadas Engine vs. SiriDB

System Properties Comparison Databricks vs. Google Cloud Firestore vs. Sadas Engine vs. SiriDB

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Editorial information provided by DB-Engines

Name

Description

The Databricks Lakehouse Platform combines elements of data lakes and data warehouses to provide a unified view onto structured and unstructured data. It is based on Apache Spark.

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.

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

Open Source Time Series DBMS

Primary database model

Document store
Relational DBMS

Document store

Relational DBMS

Time Series DBMS

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

Score	84.24
Rank	#14	Overall
	#2	Document stores
	#9	Relational DBMS

Score	6.63
Rank	#54	Overall
	#9	Document stores

Score	0.00
Rank	#385	Overall
	#159	Relational DBMS

Score	0.00
Rank	#385	Overall
	#40	Time Series DBMS

Website

www.databricks.com

firebase.google.com/products/firestore

www.sadasengine.com

siridb.com

Technical documentation

docs.databricks.com

firebase.google.com/docs/firestore

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

docs.siridb.com

Developer

Databricks

Google

SADAS s.r.l.

Cesbit

Initial release

2013

2017

2006

2017

Current release

8.0

License

Commercial or Open Source

commercial

free trial version available

Open Source

MIT License

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++

Server operating systems

hosted

AIX
Linux
Windows

Linux

Data scheme

Flexible Schema (defined schema, partial schema, schema free)

schema-free

yes

Typing

predefined data types such as float or date

yes

Numeric data

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.

yes

Secondary indexes

yes

SQL

Support of SQL

with Databricks SQL

yes

APIs and other access methods

JDBC
ODBC
RESTful HTTP API

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

JDBC
ODBC
Proprietary protocol

HTTP API

Supported programming languages

Python
R
Scala

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

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

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

Server-side scripts

Stored procedures

user defined functions and aggregates

yes, Firebase Rules & Cloud Functions

Triggers

yes, with Cloud Functions

Partitioning methods

Methods for storing different data on different nodes

Sharding

horizontal partitioning

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Multi-source replication

none

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

Using Cloud Dataflow

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

yes

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

managed by 'Learn by Usage'

yes

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.

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

simple rights management via user accounts

More information provided by the system vendor

Specific characteristics

Supported database models : In addition to the Document store and Relational DBMS...
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More resources

DB-Engines blog posts

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2 January 2024, Matthias Gelbmann, Paul Andlinger

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Recent citations in the news

Databricks could launch IPO in two months but biding time despite investor pressure, CEO says
13 September 2024, ION Analytics

Leading Tech Talent Creation Expert Launches Databricks Data Engineer Program
19 September 2024, Business Wire

Databricks reportedly paid $2 billion in Tabular acquisition
14 August 2024, TechCrunch

Building a RAG System on Databricks With Your Unstructured Data Using Tonic Textual
21 September 2024, Security Boulevard

The People in Charge at Databricks as It Moves Toward a Potential IPO
24 July 2024, The Information

provided by Google News

Realtime vs Cloud Firestore: Which Firebase Database to Choose
8 March 2024, Appinventiv

Google's AI-First Strategy Brings Vector Support To Cloud Databases
1 March 2024, Forbes

Google launches Firebase Genkit, a new open source framework for building AI-powered apps
14 May 2024, TechCrunch

NoSQL on the Cloud With Python
7 August 2020, Towards Data Science

Google Launches Cloud NoSQL Database for Mobile, Web Apps
10 October 2017, ADT Magazine

provided by Google News

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