DBMS > AlaSQL vs. etcd vs. Google Cloud Firestore vs. Microsoft Azure AI Search vs. Microsoft Azure Cosmos DB

System Properties Comparison AlaSQL vs. etcd vs. Google Cloud Firestore vs. Microsoft Azure AI Search vs. Microsoft Azure Cosmos DB

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.

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

Globally distributed, horizontally scalable, multi-model database service

Primary database model

Document store
Relational DBMS

Key-value store

Document store

Search engine

Document store
Graph DBMS
Key-value store
Wide column store

Secondary database models

Vector DBMS

Spatial 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	7.25
Rank	#54	Overall
	#5	Key-value stores

Score	7.85
Rank	#51	Overall
	#8	Document stores

Score	5.59
Rank	#63	Overall
	#7	Search engines

Score	29.04
Rank	#27	Overall
	#4	Document stores
	#2	Graph DBMS
	#3	Key-value stores
	#3	Wide column stores

Website

alasql.org

etcd.io
github.com/etcd-io/etcd

firebase.google.com/products/firestore

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

azure.microsoft.com/services/cosmos-db

Technical documentation

github.com/AlaSQL/alasql

etcd.io/docs
github.com/etcd-io/etcd/tree/master/Documentation

firebase.google.com/docs/firestore

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

learn.microsoft.com/azure/cosmos-db

Developer

Andrey Gershun & Mathias R. Wulff

Google

Microsoft

Initial release

2014

2017

2015

2014

Current release

3.4, August 2019

License

Commercial or Open Source

Open Source

MIT-License

Open Source

Apache Version 2.0

commercial

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

Server operating systems

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

FreeBSD
Linux
Windows

experimental

hosted

Data scheme

schema-free

yes

schema-free

Typing

predefined data types such as float or date

yes

JSON types

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

All properties auto-indexed by default

SQL

Support of SQL

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

SQL-like query language

APIs and other access methods

JavaScript API

gRPC
JSON over HTTP

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

RESTful HTTP API

DocumentDB API
Graph API (Gremlin)
MongoDB API
RESTful HTTP API
Table API

Supported programming languages

JavaScript

.Net
C
C++
Clojure
Erlang
Go
Haskell
Java
JavaScript (Node.js)
Perl
PHP
Python
R
Ruby
Rust
Scala
Tcl

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

C#
Java
JavaScript
Python

.Net
C#
Java
JavaScript
JavaScript (Node.js)
MongoDB client drivers written for various programming languages
Python

Server-side scripts

Stored procedures

yes, Firebase Rules & Cloud Functions

JavaScript

Triggers

yes

yes, watching key changes

yes, with Cloud Functions

JavaScript

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

Implicit feature of the cloud service

Sharding

Implicit feature of the cloud service

Replication methods

Methods for redundantly storing data on multiple nodes

none

Using Raft consensus algorithm to ensure data replication with strong consistency among multiple replicas.

Multi-source replication

yes

Implicit feature of the cloud service

yes

Implicit feature of the cloud service

MapReduce

Offers an API for user-defined Map/Reduce methods

Using Cloud Dataflow

with Hadoop integration

Integration with Hadoop/HDInsight on Azure*

Consistency concepts

Methods to ensure consistency in a distributed system

none

Immediate Consistency

Bounded Staleness
Consistent Prefix
Eventual Consistency
Immediate Consistency

Consistency level configurable on request level
Session 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

Multi-item ACID transactions with snapshot isolation within a partition

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

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

Access rights can be defined down to the item level

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