DBMS > AlaSQL vs. Amazon Redshift vs. Firebase Realtime Database vs. Qdrant

System Properties Comparison AlaSQL vs. Amazon Redshift vs. Firebase Realtime Database vs. Qdrant

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Editorial information provided by DB-Engines

Name

Description

JavaScript DBMS library

Large scale data warehouse service for use with business intelligence tools

Cloud-hosted realtime document store. iOS, Android, and JavaScript clients share one Realtime Database instance and automatically receive updates with the newest data.

A high-performance vector database with neural network or semantic-based matching

Primary database model

Document store
Relational DBMS

Relational DBMS

Document store

Vector DBMS

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

Score	0.42
Rank	#264	Overall
	#42	Document stores
	#122	Relational DBMS

Score	15.25
Rank	#38	Overall
	#23	Relational DBMS

Score	13.60
Rank	#39	Overall
	#6	Document stores

Score	1.53
Rank	#145	Overall
	#7	Vector DBMS

Website

alasql.org

aws.amazon.com/redshift

firebase.google.com/products/realtime-database

github.com/qdrant/qdrant
qdrant.tech

Technical documentation

github.com/AlaSQL/alasql

docs.aws.amazon.com/redshift

firebase.google.com/docs/database

qdrant.tech/documentation

Developer

Andrey Gershun & Mathias R. Wulff

Amazon (based on PostgreSQL)

Google

acquired by Google 2014

Qdrant

Initial release

2014

2012

2021

License

Commercial or Open Source

Open Source

MIT-License

commercial

Open Source

Apache Version 2.0

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

Rust

Server operating systems

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

hosted

Docker
Linux
macOS
Windows

Data scheme

schema-free

yes

schema-free

Typing

predefined data types such as float or date

yes

Numbers, Strings, Geo, Boolean

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

restricted

yes

Keywords, numberic ranges, geo, full-text

SQL

Support of SQL

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

yes

does not fully support an SQL-standard

APIs and other access methods

JavaScript API

JDBC
ODBC

Android
iOS
JavaScript API
RESTful HTTP API

gRPC
OpenAPI 3.0
RESTful HTTP/JSON API

OpenAPI 3.0

Supported programming languages

JavaScript

All languages supporting JDBC/ODBC

Java
JavaScript
Objective-C

.Net
Go
Java
JavaScript (Node.js)
Python
Rust

Server-side scripts

Stored procedures

user defined functions

in Python

limited functionality with using 'rules'

Triggers

yes

Callbacks are triggered when data changes

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

none

yes

Collection-level replication

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

none

Immediate Consistency

Eventual Consistency

if the client is offline
Immediate Consistency

if the client is online

Eventual Consistency, tunable consistency

Foreign keys

Referential integrity

yes

informational only, not enforced by the system

Transaction concepts

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

yes

only for local storage and DOM-storage

ACID

yes

Concurrency

Support for concurrent manipulation of data

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

fine grained access rights according to SQL-standard

yes, based on authentication and database rules

Key-based authentication

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