DBMS > Google Cloud Firestore vs. PouchDB vs. SAP Adaptive Server vs. SQLite

System Properties Comparison Google Cloud Firestore vs. PouchDB vs. SAP Adaptive Server vs. SQLite

Please select another system to include it in the comparison.

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.

JavaScript DBMS with an API inspired by CouchDB

The SAP (Sybase) Adaptive Server Enterprise (ASE) is an enterprise-class RDBMS

Widely used embeddable, in-process RDBMS

Primary database model

Document store

Relational DBMS

Secondary database models

Spatial DBMS

with Boeing's Spatial Query Server

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

Score	8.96
Rank	#48	Overall
	#8	Document stores

Score	2.35
Rank	#116	Overall
	#22	Document stores

Score	37.12
Rank	#25	Overall
	#17	Relational DBMS

Score	116.01
Rank	#10	Overall
	#7	Relational DBMS

Website

firebase.google.com/products/firestore

pouchdb.com

www.sap.com/products/technology-platform/sybase-ase.html

www.sqlite.org

Technical documentation

firebase.google.com/docs/firestore

pouchdb.com/guides

help.sap.com/docs/SAP_ASE

www.sqlite.org/docs.html

Developer

Google

Apache Software Foundation

SAP, Sybase

Dwayne Richard Hipp

Initial release

2017

2012

1987

2000

Current release

7.1.1, June 2019

16.0

3.45.2 (12 March 2024), March 2024

License

Commercial or Open Source

commercial

Open Source

commercial

Open Source

Public Domain

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

JavaScript

C and C++

Server operating systems

hosted

server-less, requires a JavaScript environment (browser, Node.js)

AIX
HP-UX
Linux
Solaris
Unix
Windows

server-less

Data scheme

schema-free

yes

dynamic column types

Typing

predefined data types such as float or date

yes

not rigid because of 'dynamic typing' concept.

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

via views

yes

SQL

Support of SQL

yes

SQL-92 is not fully supported

APIs and other access methods

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

HTTP REST

only for PouchDB Server
JavaScript API

ADO.NET
JDBC
ODBC
OLE DB
Tabular Data Stream (TDS)

ADO.NET

inofficial driver
JDBC

inofficial driver
ODBC

inofficial driver

Supported programming languages

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

JavaScript

C
C++
Cobol
Java
Java
Perl
PHP
Python

Actionscript
Ada
Basic
C
C#
C++
D
Delphi
Forth
Fortran
Haskell
Java
JavaScript
Lisp
Lua
MatLab
Objective-C
OCaml
Perl
PHP
PL/SQL
Python
R
Ruby
Scala
Scheme
Smalltalk
Tcl

Server-side scripts

Stored procedures

yes, Firebase Rules & Cloud Functions

View functions in JavaScript

Java and Transact-SQL

Triggers

yes, with Cloud Functions

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

with a proxy-based framework, named couchdb-lounge

horizontal partitioning

none

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication

also with CouchDB databases
Source-replica replication

also with CouchDB databases

Multi-source replication
Source-replica replication

none

MapReduce

Offers an API for user-defined Map/Reduce methods

Using Cloud Dataflow

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual 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

via file-system locks

Durability

Support for making data persistent

yes

by using IndexedDB, WebSQL or LevelDB as backend

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

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

We invite representatives of system vendors to contact us for updating and extending the system information,
and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.