DBMS > Microsoft SQL Server vs. MonetDB vs. Rockset vs. Sadas Engine vs. Teradata Aster

System Properties Comparison Microsoft SQL Server vs. MonetDB vs. Rockset vs. Sadas Engine vs. Teradata Aster

Editorial information provided by DB-Engines

Name

Teradata Aster has been integrated into other Teradata systems and therefore will be removed from the DB-Engines ranking.

Description

Microsofts flagship relational DBMS

A relational database management system that stores data in columns

A scalable, reliable search and analytics service in the cloud, built on RocksDB

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

Platform for big data analytics on multistructured data sources and types

Primary database model

Relational DBMS

Document store

Relational DBMS

Secondary database models

Document store
Graph DBMS
Spatial DBMS

Document store
Spatial DBMS

Relational DBMS
Search engine

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

Score	821.56
Rank	#3	Overall
	#3	Relational DBMS

Score	1.72
Rank	#141	Overall
	#64	Relational DBMS

Score	0.82
Rank	#212	Overall
	#36	Document stores

Score	0.07
Rank	#373	Overall
	#157	Relational DBMS

Website

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

www.monetdb.org

rockset.com

www.sadasengine.com

Technical documentation

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

www.monetdb.org/Documentation

docs.rockset.com

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

Developer

Microsoft

MonetDB BV

Rockset

SADAS s.r.l.

Teradata

Initial release

1989

2004

2019

2006

2005

Current release

SQL Server 2022, November 2022

Dec2023 (11.49), December 2023

8.0

License

Commercial or Open Source

commercial

restricted free version is available

Open Source

Mozilla Public License 2.0

commercial

free trial version available

commercial

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

C++

Server operating systems

Linux
Windows

FreeBSD
Linux
OS X
Solaris
Windows

hosted

AIX
Linux
Windows

Linux

Data scheme

yes

schema-free

yes

Flexible Schema (defined schema, partial schema, schema free)

defined schema within the relational store; partial schema or schema free in the Aster File Store

Typing

predefined data types such as float or date

yes

dynamic typing

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

ingestion from XML files supported

yes

in Aster File Store

Secondary indexes

yes

all fields are automatically indexed

yes

SQL

Support of SQL

yes

SQL 2003 with some extensions

Read-only SQL queries, including JOINs

yes

APIs and other access methods

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

JDBC
native C library

MAPI library (MonetDB application programming interface)
ODBC

HTTP REST

JDBC
ODBC
Proprietary protocol

ADO.NET
JDBC
ODBC
OLE DB

Supported programming languages

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

C
C++
Java
JavaScript (Node.js)
Perl
PHP
Python
R
Ruby

Go
Java
JavaScript (Node.js)
Python

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

C
C#
C++
Java
Python
R

Server-side scripts

Stored procedures

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

yes, in SQL, C, R

R packages

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

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

Sharding via remote tables

Automatic sharding

horizontal partitioning

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

yes, but depending on the SQL-Server Edition

none

Source-replica replication available in experimental status

yes

none

yes

Dimension tables are replicated across all nodes in the cluster. The number of replicas for the file store can be configured.

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

SQL Map-Reduce Framework

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency

Immediate Consistency

Immediate Consistency or Eventual Consistency depending on configuration

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

Durability

Support for making data persistent

yes

In-memory capabilities

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

yes

managed by 'Learn by Usage'

User concepts

Access control

fine grained access rights according to SQL-standard

Access rights for users and organizations can be defined via Rockset console

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

fine grained access rights according to SQL-standard

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