DBMS > EXASOL vs. Microsoft SQL Server vs. Postgres-XL vs. Riak KV vs. Snowflake

System Properties Comparison EXASOL vs. Microsoft SQL Server vs. Postgres-XL vs. Riak KV vs. Snowflake

Editorial information provided by DB-Engines

Name

Description

High-performance, in-memory, MPP database specifically designed for in-memory analytics.

Microsofts flagship relational DBMS

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

Distributed, fault tolerant key-value store

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

Primary database model

Relational DBMS

Key-value store

with links between data sets and object tags for the creation of secondary indexes

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	1.99
Rank	#124	Overall
	#58	Relational DBMS

Score	824.29
Rank	#3	Overall
	#3	Relational DBMS

Score	0.49
Rank	#256	Overall
	#117	Relational DBMS

Score	4.10
Rank	#82	Overall
	#9	Key-value stores

Score	121.33
Rank	#9	Overall
	#6	Relational DBMS

Website

www.exasol.com

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

www.postgres-xl.org

www.snowflake.com

Technical documentation

www.exasol.com/resources

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

www.postgres-xl.org/documentation

www.tiot.jp/riak-docs/riak/kv/latest

docs.snowflake.net/manuals/index.html

Developer

Exasol

Microsoft

OpenSource, formerly Basho Technologies

Snowflake Computing Inc.

Initial release

2000

1989

2014

since 2012, originally named StormDB

2009

2014

Current release

SQL Server 2022, November 2022

10 R1, October 2018

3.2.0, December 2022

License

Commercial or Open Source

commercial

restricted free version is available

Open Source

Mozilla public license

Open Source

Apache version 2, commercial enterprise edition

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

C++

Erlang

Server operating systems

Linux
Windows

Linux
macOS

Linux
OS X

hosted

Data scheme

yes

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

restricted

SQL

Support of SQL

yes

distributed, parallel query execution

yes

APIs and other access methods

.Net
JDBC
ODBC
WebSocket

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

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

HTTP API
Native Erlang Interface

CLI Client
JDBC
ODBC

Supported programming languages

Java
Lua
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

unofficial client library
C#
C++

unofficial client library
Clojure

unofficial client library
Dart

unofficial client library
Erlang
Go

unofficial client library
Groovy

unofficial client library
Haskell

unofficial client library
Java
JavaScript

unofficial client library
Lisp

unofficial client library
Perl

unofficial client library
PHP
Python
Ruby
Scala

unofficial client library
Smalltalk

unofficial client library

JavaScript (Node.js)
Python

Server-side scripts

Stored procedures

user defined functions

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

user defined functions

Erlang

user defined functions

Triggers

yes

pre-commit hooks and post-commit hooks

similar concept for controling cloud resources

Partitioning methods

Methods for storing different data on different nodes

Sharding

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

horizontal partitioning

Sharding

no "single point of failure"

yes

Replication methods

Methods for redundantly storing data on multiple nodes

yes, but depending on the SQL-Server Edition

selectable replication factor

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Hadoop integration

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency

Immediate Consistency

Foreign keys

Referential integrity

yes

links between data sets can be stored

yes

Transaction concepts

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

ACID

MVCC

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

User concepts

Access control

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

fine grained access rights according to SQL-standard

yes, using Riak Security

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

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