DBMS > AlaSQL vs. Amazon DynamoDB vs. Microsoft Azure Cosmos DB vs. Spark SQL

System Properties Comparison AlaSQL vs. Amazon DynamoDB vs. Microsoft Azure Cosmos DB vs. Spark SQL

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Editorial information provided by DB-Engines

Name

Description

JavaScript DBMS library

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

Globally distributed, horizontally scalable, multi-model database service

Spark SQL is a component on top of 'Spark Core' for structured data processing

Primary database model

Document store
Relational DBMS

Document store
Key-value store

Document store
Graph DBMS
Key-value store
Wide column store

Relational DBMS

Secondary database models

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

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

Score	18.96
Rank	#33	Overall
	#20	Relational DBMS

Website

alasql.org

aws.amazon.com/dynamodb

azure.microsoft.com/services/cosmos-db

spark.apache.org/sql

Technical documentation

github.com/AlaSQL/alasql

docs.aws.amazon.com/dynamodb

learn.microsoft.com/azure/cosmos-db

spark.apache.org/docs/latest/sql-programming-guide.html

Developer

Andrey Gershun & Mathias R. Wulff

Amazon

Microsoft

Apache Software Foundation

Initial release

2014

2012

2014

Current release

3.5.0 ( 2.13), September 2023

License

Commercial or Open Source

Open Source

MIT-License

commercial

free tier for a limited amount of database operations

commercial

Open Source

Apache 2.0

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

Scala

Server operating systems

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

hosted

Linux
OS X
Windows

Data scheme

schema-free

yes

Typing

predefined data types such as float or date

yes

JSON types

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

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

SQL-like DML and DDL statements

APIs and other access methods

JavaScript API

RESTful HTTP API

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

JDBC
ODBC

Supported programming languages

JavaScript

.Net
ColdFusion
Erlang
Groovy
Java
JavaScript
Perl
PHP
Python
Ruby

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

Java
Python
R
Scala

Server-side scripts

Stored procedures

JavaScript

Triggers

yes

by integration with AWS Lambda

JavaScript

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

Implicit feature of the cloud service

yes, utilizing Spark Core

Replication methods

Methods for redundantly storing data on multiple nodes

none

yes

Implicit feature of the cloud service

none

MapReduce

Offers an API for user-defined Map/Reduce methods

may be implemented via Amazon Elastic MapReduce (Amazon EMR)

with Hadoop integration

Integration with Hadoop/HDInsight on Azure*

Consistency concepts

Methods to ensure consistency in a distributed system

none

Eventual Consistency
Immediate Consistency

can be specified for read operations

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

ACID

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

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

Access rights can be defined down to the item level

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