DBMS > AlaSQL vs. Alibaba Cloud AnalyticDB for PostgreSQL vs. Microsoft SQL Server vs. Postgres-XL vs. Quasardb

System Properties Comparison AlaSQL vs. Alibaba Cloud AnalyticDB for PostgreSQL vs. Microsoft SQL Server vs. Postgres-XL vs. Quasardb

Editorial information provided by DB-Engines

Name

Description

JavaScript DBMS library

An online MPP (Massively Parallel Processing) data warehousing service based on Greenplum

Microsofts flagship relational DBMS

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

Distributed, high-performance timeseries database

Primary database model

Document store
Relational DBMS

Relational DBMS

Time Series 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	0.68
Rank	#231	Overall
	#105	Relational DBMS

Score	824.29
Rank	#3	Overall
	#3	Relational DBMS

Score	0.49
Rank	#256	Overall
	#117	Relational DBMS

Score	0.14
Rank	#332	Overall
	#29	Time Series DBMS

Website

alasql.org

www.alibabacloud.com/product/hybriddb-postgresql

www.microsoft.com/en-us/sql-server

www.postgres-xl.org

quasar.ai

Technical documentation

github.com/AlaSQL/alasql

www.alibabacloud.com/help/en/analyticdb-for-postgresql/latest/product-introduction-overview

learn.microsoft.com/en-US/sql/sql-server

www.postgres-xl.org/documentation

doc.quasar.ai/master

Developer

Andrey Gershun & Mathias R. Wulff

Alibaba / Pivotal Software Inc. / PostgreSQL Global Development Group

Microsoft

quasardb

Initial release

2014

2016

1989

2014

since 2012, originally named StormDB

2009

Current release

SQL Server 2022, November 2022

10 R1, October 2018

3.14.1, January 2024

License

Commercial or Open Source

Open Source

MIT-License

commercial

restricted free version is available

Open Source

Mozilla public license

commercial

Free community edition, Non-profit organizations and non-commercial usage are eligible for free licenses

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

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Implementation language

JavaScript

C++

Server operating systems

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

hosted

Linux
Windows

Linux
macOS

BSD
Linux
OS X
Windows

Data scheme

schema-free

yes

schema-free

Typing

predefined data types such as float or date

yes

integer and binary

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

Secondary indexes

yes

with tags

SQL

Support of SQL

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

yes

distributed, parallel query execution

SQL-like query language

APIs and other access methods

JavaScript API

JDBC
ODBC

ADO.NET
JDBC
ODBC
OLE DB
Tabular Data Stream (TDS)

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

HTTP API

Supported programming languages

JavaScript

C
Java
Perl
Python
R

C#
C++
Delphi
Go
Java
JavaScript (Node.js)
PHP
Python
R
Ruby
Visual Basic

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

.Net
C
C#
C++
Go
Java
JavaScript (Node.js)
PHP
Python
R

Server-side scripts

Stored procedures

yes

Transact SQL, .NET languages, R, Python and (with SQL Server 2019) Java

user defined functions

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

Implicit feature of the cloud service

tables can be distributed across several files (horizontal partitioning); sharding through federation

horizontal partitioning

Sharding

consistent hashing

Replication methods

Methods for redundantly storing data on multiple nodes

none

yes

Implicit feature of the cloud service

yes, but depending on the SQL-Server Edition

Source-replica replication with selectable replication factor

MapReduce

Offers an API for user-defined Map/Reduce methods

with Hadoop integration

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

by using LevelDB

In-memory capabilities

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

yes

Transient mode

User concepts

Access control

fine grained access rights according to SQL-standard

Cryptographically strong user authentication and audit trail

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