DBMS > Google Cloud Firestore vs. Microsoft Azure AI Search vs. Postgres-XL vs. SWC-DB

System Properties Comparison Google Cloud Firestore vs. Microsoft Azure AI Search vs. Postgres-XL vs. SWC-DB

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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.

Search-as-a-service for web and mobile app development

Based on PostgreSQL enhanced with MPP and write-scale-out cluster features

A high performance, scalable Wide Column DBMS

Primary database model

Secondary database models

Vector DBMS

Document store
Spatial DBMS

Time Series DBMS

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

Score	7.85
Rank	#51	Overall
	#8	Document stores

Score	5.59
Rank	#63	Overall
	#7	Search engines

Score	0.49
Rank	#256	Overall
	#117	Relational DBMS

Score	0.01
Rank	#376	Overall
	#13	Wide column stores

Website

firebase.google.com/products/firestore

azure.microsoft.com/en-us/services/search

www.postgres-xl.org

github.com/kashirin-alex/swc-db
www.swcdb.org

Technical documentation

firebase.google.com/docs/firestore

learn.microsoft.com/en-us/azure/search

www.postgres-xl.org/documentation

Developer

Google

Microsoft

Alex Kashirin

Initial release

2017

2015

2014

since 2012, originally named StormDB

2020

Current release

10 R1, October 2018

0.5, April 2021

License

Commercial or Open Source

commercial

Open Source

Mozilla public license

Open Source

GPL V3

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

Linux
macOS

Linux

Data scheme

schema-free

yes

schema-free

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.

yes

XML type, but no XML query functionality

Secondary indexes

yes

SQL

Support of SQL

yes

distributed, parallel query execution

SQL-like query language

APIs and other access methods

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

RESTful HTTP API

ADO.NET
JDBC
native C library
ODBC
streaming API for large objects

Proprietary protocol
Thrift

Supported programming languages

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

C#
Java
JavaScript
Python

.Net
C
C++
Delphi
Erlang
Java
JavaScript (Node.js)
Perl
PHP
Python
Tcl

C++

Server-side scripts

Stored procedures

yes, Firebase Rules & Cloud Functions

user defined functions

Triggers

yes, with Cloud Functions

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

Implicit feature of the cloud service

horizontal partitioning

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication

yes

Implicit feature of the cloud service

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

yes

ACID

MVCC

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.

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.

yes

using Azure authentication

fine grained access rights according to SQL-standard

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More resources

DB-Engines blog posts

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12 December 2019, Paul Andlinger

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