DBMS > EDB Postgres vs. HEAVY.AI vs. Microsoft SQL Server vs. Quasardb vs. Sadas Engine

System Properties Comparison EDB Postgres vs. HEAVY.AI vs. Microsoft SQL Server vs. Quasardb vs. Sadas Engine

Editorial information provided by DB-Engines

Name

Description

The EDB Postgres Platform is an enterprise-class data management platform based on the open source database PostgreSQL with flexible deployment options and Oracle compatibility features, complemented by tool kits for management, integration, and migration.

A high performance, column-oriented RDBMS, specifically developed to harness the massive parallelism of modern CPU and GPU hardware

Microsofts flagship relational DBMS

Distributed, high-performance timeseries database

SADAS Engine is a columnar DBMS specifically designed for high performance in data warehouse environments

Primary database model

Relational DBMS

Time Series DBMS

Relational DBMS

Secondary database models

Document store
Spatial DBMS

Spatial DBMS

Document store
Graph DBMS
Spatial DBMS

DB-Engines Ranking measures the popularity of database management systems
Trend Chart

Score	1.86
Rank	#131	Overall
	#61	Relational DBMS

Score	1.41
Rank	#153	Overall
	#71	Relational DBMS

Score	807.76
Rank	#3	Overall
	#3	Relational DBMS

Score	0.13
Rank	#332	Overall
	#28	Time Series DBMS

Score	0.00
Rank	#385	Overall
	#159	Relational DBMS

Website

www.enterprisedb.com

github.com/heavyai/heavydb
www.heavy.ai

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

quasar.ai

www.sadasengine.com

Technical documentation

www.enterprisedb.com/docs

docs.heavy.ai

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

doc.quasar.ai/master

www.sadasengine.com/en/sadas-engine-download-free-trial-and-documentation/#documentation

Developer

EnterpriseDB

HEAVY.AI, Inc.

Microsoft

quasardb

SADAS s.r.l.

Initial release

2005

2016

1989

2009

2006

Current release

14, December 2021

5.10, January 2022

SQL Server 2022, November 2022

3.14.1, January 2024

8.0

License

Commercial or Open Source

commercial

BSD for PostgreSQL-components

Open Source

Apache Version 2; enterprise edition available

commercial

restricted free version is available

commercial

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

commercial

free trial version available

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

C++ and CUDA

C++

Server operating systems

Linux
Windows

Linux

Linux
Windows

BSD
Linux
OS X
Windows

AIX
Linux
Windows

Data scheme

yes

schema-free

yes

Typing

predefined data types such as float or date

yes

integer and binary

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

specific XML-type available, but no XML query functionality.

yes

Secondary indexes

yes

with tags

yes

SQL

Support of SQL

yes

standard with numerous extensions

yes

SQL-like query language

yes

APIs and other access methods

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

JDBC
ODBC
Thrift
Vega

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

HTTP API

JDBC
ODBC
Proprietary protocol

Supported programming languages

.Net
C
C++
Delphi
Java
Perl
PHP
Python
Tcl

All languages supporting JDBC/ODBC/Thrift
Python

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

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

.Net
C
C#
C++
Groovy
Java
PHP
Python

Server-side scripts

Stored procedures

user defined functions

realized in proprietary language PL/pgSQL or with common languages like Perl, Python, Tcl etc.

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

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

horizontal partitioning

by hash, list or range

Sharding

Round robin

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

Sharding

consistent hashing

horizontal partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication

yes, but depending on the SQL-Server Edition

Source-replica replication with selectable replication factor

none

MapReduce

Offers an API for user-defined Map/Reduce methods

with Hadoop integration

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

Support to ensure data integrity after non-atomic manipulations of data

ACID

Concurrency

Support for concurrent manipulation of data

yes, multi-version concurrency control (MVCC)

yes

Durability

Support for making data persistent

yes

by using LevelDB

yes

In-memory capabilities

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

yes

Transient mode

yes

managed by 'Learn by Usage'

User concepts

Access control

fine grained access rights according to SQL-standard

Cryptographically strong user authentication and audit trail

Access rights for users, groups and roles according to SQL-standard

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