DBMS > AlaSQL vs. Google Cloud Firestore vs. HarperDB vs. PostGIS vs. SQLite

System Properties Comparison AlaSQL vs. Google Cloud Firestore vs. HarperDB vs. PostGIS vs. SQLite

Editorial information provided by DB-Engines

Name

Description

JavaScript DBMS library

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.

Ultra-low latency distributed database with an intuitive REST API supporting NoSQL and SQL (including joins). Deployment of functions and databases simultaneously with a consolidated node-level architecture.

Spatial extension of PostgreSQL

Widely used embeddable, in-process RDBMS

Primary database model

Document store
Relational DBMS

Document store

Spatial DBMS

Relational DBMS

Secondary database models

Relational DBMS

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

Score	0.46
Rank	#260	Overall
	#40	Document stores
	#121	Relational DBMS

Score	7.85
Rank	#51	Overall
	#8	Document stores

Score	0.55
Rank	#248	Overall
	#38	Document stores

Score	22.69
Rank	#29	Overall
	#1	Spatial DBMS

Score	114.32
Rank	#10	Overall
	#7	Relational DBMS

Website

alasql.org

firebase.google.com/products/firestore

www.harperdb.io

postgis.net

www.sqlite.org

Technical documentation

github.com/AlaSQL/alasql

firebase.google.com/docs/firestore

docs.harperdb.io/docs

postgis.net/documentation

www.sqlite.org/docs.html

Developer

Andrey Gershun & Mathias R. Wulff

Google

HarperDB

Dwayne Richard Hipp

Initial release

2014

2017

2005

2000

Current release

3.1, August 2021

3.4.2, February 2024

3.45.3 (15 April 2024), April 2024

License

Commercial or Open Source

Open Source

MIT-License

commercial

free community edition available

Open Source

GPL v2.0

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

Node.js

Server operating systems

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

hosted

Linux
OS X

server-less

Data scheme

schema-free

dynamic schema

yes

dynamic column types

Typing

predefined data types such as float or date

yes

JSON data types

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.

yes

Secondary indexes

yes

SQL

Support of SQL

Close to SQL99, but no user access control, stored procedures and host language bindings.

SQL-like data manipulation statements

yes

SQL-92 is not fully supported

APIs and other access methods

JavaScript API

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

JDBC
ODBC
React Hooks
RESTful HTTP/JSON API
WebSocket

ADO.NET

inofficial driver
JDBC

inofficial driver
ODBC

inofficial driver

Supported programming languages

JavaScript

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

.Net
C
C#
C++
ColdFusion
D
Dart
Delphi
Erlang
Go
Haskell
Java
JavaScript (Node.js)
Lisp
MatLab
Objective C
Perl
PHP
PowerShell
Prolog
Python
R
Ruby
Rust
Scala
Swift

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

Custom Functions

since release 3.1

user defined functions

Triggers

yes

yes, with Cloud Functions

yes

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

A table resides as a whole on one (or more) nodes in a cluster

yes

based on PostgreSQL

none

Replication methods

Methods for redundantly storing data on multiple nodes

none

Multi-source replication

yes

the nodes on which a table resides can be defined

yes

based on PostgreSQL

none

MapReduce

Offers an API for user-defined Map/Reduce methods

Using Cloud Dataflow

Consistency concepts

Methods to ensure consistency in a distributed system

none

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

yes

only for local storage and DOM-storage

yes

Atomic execution of specific operations

ACID

Concurrency

Support for concurrent manipulation of data

yes

via file-system locks

Durability

Support for making data persistent

yes

by using IndexedDB, SQL.JS or proprietary FileStorage

yes

yes, using LMDB

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.

Access rights for users and roles

yes

based on PostgreSQL

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