DBMS > AlaSQL vs. Datomic vs. Microsoft Azure SQL Database vs. Postgres-XL vs. Snowflake

System Properties Comparison AlaSQL vs. Datomic vs. Microsoft Azure SQL Database vs. Postgres-XL vs. Snowflake

Editorial information provided by DB-Engines

Name

Description

JavaScript DBMS library

Datomic builds on immutable values, supports point-in-time queries and uses 3rd party systems for durability

Database as a Service offering with high compatibility to Microsoft SQL Server

Based on PostgreSQL enhanced with MPP and write-scale-out cluster features

Cloud-based data warehousing service for structured and semi-structured data

Primary database model

Document store
Relational DBMS

Relational DBMS

Secondary database models

Document store
Graph DBMS
Spatial DBMS

Document store
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	1.59
Rank	#150	Overall
	#69	Relational DBMS

Score	77.99
Rank	#16	Overall
	#11	Relational DBMS

Score	0.49
Rank	#256	Overall
	#117	Relational DBMS

Score	121.33
Rank	#9	Overall
	#6	Relational DBMS

Website

alasql.org

www.datomic.com

azure.microsoft.com/en-us/products/azure-sql/database

www.postgres-xl.org

www.snowflake.com

Technical documentation

github.com/AlaSQL/alasql

docs.datomic.com

docs.microsoft.com/en-us/azure/azure-sql

www.postgres-xl.org/documentation

docs.snowflake.net/manuals/index.html

Developer

Andrey Gershun & Mathias R. Wulff

Cognitect

Microsoft

Snowflake Computing Inc.

Initial release

2014

2012

2010

2014

since 2012, originally named StormDB

2014

Current release

1.0.6735, June 2023

V12

10 R1, October 2018

License

Commercial or Open Source

Open Source

MIT-License

commercial

limited edition free

commercial

Open Source

Mozilla public license

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

Java, Clojure

C++

Server operating systems

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

All OS with a Java VM

hosted

Linux
macOS

hosted

Data scheme

schema-free

yes

support of semi-structured data formats (JSON, XML, Avro)

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

XML type, but no XML query functionality

yes

Secondary indexes

yes

SQL

Support of SQL

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

yes

distributed, parallel query execution

yes

APIs and other access methods

JavaScript API

RESTful HTTP API

ADO.NET
JDBC
ODBC

ADO.NET
JDBC
native C library
ODBC
streaming API for large objects

CLI Client
JDBC
ODBC

Supported programming languages

JavaScript

Clojure
Java

.Net
C#
Java
JavaScript (Node.js)
PHP
Python
Ruby

.Net
C
C++
Delphi
Erlang
Java
JavaScript (Node.js)
Perl
PHP
Python
Tcl

JavaScript (Node.js)
Python

Server-side scripts

Stored procedures

yes

Transaction Functions

Transact SQL

user defined functions

Triggers

yes

By using transaction functions

yes

similar concept for controling cloud resources

Partitioning methods

Methods for storing different data on different nodes

none

But extensive use of caching in the application peers

horizontal partitioning

yes

Replication methods

Methods for redundantly storing data on multiple nodes

none

But extensive use of caching in the application peers

yes, with always 3 replicas available

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

none

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

MVCC

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

by using IndexedDB, SQL.JS or proprietary FileStorage

yes

using external storage systems (e.g. Cassandra, DynamoDB, PostgreSQL, Couchbase and others)

yes

In-memory capabilities

Is there an option to define some or all structures to be held in-memory only.

yes

recommended only for testing and development

User concepts

Access control

fine grained access rights according to SQL-standard

Users with fine-grained authorization concept, user roles and pluggable authentication

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