DBMS > AlaSQL vs. Google Cloud Firestore vs. H2 vs. PostGIS vs. Riak KV

System Properties Comparison AlaSQL vs. Google Cloud Firestore vs. H2 vs. PostGIS vs. Riak KV

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.

Full-featured RDBMS with a small footprint, either embedded into a Java application or used as a database server.

Spatial extension of PostgreSQL

Distributed, fault tolerant key-value store

Primary database model

Document store
Relational DBMS

with links between data sets and object tags for the creation of secondary indexes

Secondary database models

Spatial DBMS

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	8.13
Rank	#49	Overall
	#31	Relational DBMS

Score	22.69
Rank	#29	Overall
	#1	Spatial DBMS

Score	4.10
Rank	#82	Overall
	#9	Key-value stores

Website

alasql.org

firebase.google.com/products/firestore

www.h2database.com

postgis.net

Technical documentation

github.com/AlaSQL/alasql

firebase.google.com/docs/firestore

www.h2database.com/html/main.html

postgis.net/documentation

www.tiot.jp/riak-docs/riak/kv/latest

Developer

Andrey Gershun & Mathias R. Wulff

Google

Thomas Mueller

OpenSource, formerly Basho Technologies

Initial release

2014

2017

2005

2009

Current release

2.2.220, July 2023

3.4.2, February 2024

3.2.0, December 2022

License

Commercial or Open Source

Open Source

MIT-License

commercial

Open Source

dual-licence (Mozilla public license, Eclipse public license)

Open Source

GPL v2.0

Open Source

Apache version 2, commercial enterprise edition

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

Java

Erlang

Server operating systems

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

hosted

All OS with a Java VM

Linux
OS X

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

Secondary indexes

yes

restricted

SQL

Support of SQL

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

yes

APIs and other access methods

JavaScript API

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

JDBC
ODBC

HTTP API
Native Erlang Interface

Supported programming languages

JavaScript

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

Java

unofficial client library
C#
C++

unofficial client library
Clojure

unofficial client library
Dart

unofficial client library
Erlang
Go

unofficial client library
Groovy

unofficial client library
Haskell

unofficial client library
Java
JavaScript

unofficial client library
Lisp

unofficial client library
Perl

unofficial client library
PHP
Python
Ruby
Scala

unofficial client library
Smalltalk

unofficial client library

Server-side scripts

Stored procedures

yes, Firebase Rules & Cloud Functions

Java Stored Procedures and User-Defined Functions

user defined functions

Erlang

Triggers

yes

yes, with Cloud Functions

yes

pre-commit hooks and post-commit hooks

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

none

yes

based on PostgreSQL

Sharding

no "single point of failure"

Replication methods

Methods for redundantly storing data on multiple nodes

none

Multi-source replication

With clustering: 2 database servers on different computers operate on identical copies of a database

yes

based on PostgreSQL

selectable replication factor

MapReduce

Offers an API for user-defined Map/Reduce methods

Using Cloud Dataflow

yes

Consistency concepts

Methods to ensure consistency in a distributed system

none

Immediate Consistency

Eventual Consistency

Foreign keys

Referential integrity

yes

links between data sets can be stored

Transaction concepts

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

yes

only for local storage and DOM-storage

yes

ACID

Concurrency

Support for concurrent manipulation of data

yes

yes, multi-version concurrency control (MVCC)

yes

Durability

Support for making data persistent

yes

by using IndexedDB, SQL.JS or proprietary FileStorage

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

yes

based on PostgreSQL

yes, using Riak Security

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More resources

DB-Engines blog posts

Cloud-based DBMS's popularity grows at high rates
12 December 2019, Paul Andlinger

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6 April 2021, Matthias Gelbmann

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