DBMS > AlaSQL vs. Amazon DynamoDB vs. Drizzle vs. Google Cloud Firestore vs. YottaDB

System Properties Comparison AlaSQL vs. Amazon DynamoDB vs. Drizzle vs. Google Cloud Firestore vs. YottaDB

Editorial information provided by DB-Engines

Name

Drizzle has published its last release in September 2012. The open-source project is discontinued and Drizzle is excluded from the DB-Engines ranking.

Description

JavaScript DBMS library

Hosted, scalable database service by Amazon with the data stored in Amazons cloud

MySQL fork with a pluggable micro-kernel and with an emphasis of performance over compatibility.

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.

A fast and solid embedded Key-value store

Primary database model

Document store
Relational DBMS

Document store
Key-value store

Relational DBMS

Document store

Key-value store

Secondary database models

Relational DBMS

using the Octo plugin

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	74.07
Rank	#17	Overall
	#3	Document stores
	#2	Key-value stores

Score	7.85
Rank	#51	Overall
	#8	Document stores

Score	0.20
Rank	#317	Overall
	#47	Key-value stores

Website

alasql.org

aws.amazon.com/dynamodb

firebase.google.com/products/firestore

yottadb.com

Technical documentation

github.com/AlaSQL/alasql

docs.aws.amazon.com/dynamodb

firebase.google.com/docs/firestore

yottadb.com/resources/documentation

Developer

Andrey Gershun & Mathias R. Wulff

Amazon

Drizzle project, originally started by Brian Aker

Google

YottaDB, LLC

Initial release

2014

2012

2008

2017

2001

Current release

7.2.4, September 2012

License

Commercial or Open Source

Open Source

MIT-License

commercial

free tier for a limited amount of database operations

Open Source

GNU GPL

commercial

Open Source

AGPL 3.0

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

JavaScript

C++

Server operating systems

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

hosted

FreeBSD
Linux
OS X

hosted

Docker
Linux

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.

Secondary indexes

yes

SQL

Support of SQL

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

yes

with proprietary extensions

by using the Octo plugin

APIs and other access methods

JavaScript API

RESTful HTTP API

JDBC

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

PostgreSQL wire protocol

using the Octo plugin
Proprietary protocol

Supported programming languages

JavaScript

.Net
ColdFusion
Erlang
Groovy
Java
JavaScript
Perl
PHP
Python
Ruby

C
C++
Java
PHP

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

C
Go
JavaScript (Node.js)
Lua
M
Perl
Python
Rust

Server-side scripts

Stored procedures

yes, Firebase Rules & Cloud Functions

Triggers

yes

by integration with AWS Lambda

hooks for callbacks inside the server can be used.

yes, with Cloud Functions

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

none

yes

Multi-source replication
Source-replica replication

Multi-source replication

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

may be implemented via Amazon Elastic MapReduce (Amazon EMR)

Using Cloud Dataflow

Consistency concepts

Methods to ensure consistency in a distributed system

none

Eventual Consistency
Immediate Consistency

can be specified for read operations

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

ACID

ACID across one or more tables within a single AWS account and region

ACID

yes

optimistic locking

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 and roles can be defined via the AWS Identity and Access Management (IAM)

Pluggable authentication mechanisms

e.g. LDAP, HTTP

Access rights for users, groups and roles based on Google Cloud Identity and Access Management. Security Rules for 3rd party authentication using Firebase Auth.

Users and groups based on OS-security mechanisms

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