DBMS > EXASOL vs. GeoMesa vs. IBM Db2 warehouse vs. Microsoft SQL Server

System Properties Comparison EXASOL vs. GeoMesa vs. IBM Db2 warehouse vs. Microsoft SQL Server

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Editorial information provided by DB-Engines

Name

Description

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

GeoMesa is a distributed spatio-temporal DBMS based on various systems as storage layer.

Cloud-based data warehousing service

Microsofts flagship relational DBMS

Primary database model

Relational DBMS

Spatial DBMS

Relational DBMS

Secondary database models

Document store
Graph DBMS
Spatial DBMS

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

Score	1.66
Rank	#138	Overall
	#64	Relational DBMS

Score	0.78
Rank	#214	Overall
	#4	Spatial DBMS

Score	1.26
Rank	#162	Overall
	#73	Relational DBMS

Score	807.76
Rank	#3	Overall
	#3	Relational DBMS

Website

www.exasol.com

www.geomesa.org

www.ibm.com/products/db2/warehouse

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

Technical documentation

www.exasol.com/resources

www.geomesa.org/documentation/stable/user/index.html

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

Developer

Exasol

CCRi and others

IBM

Microsoft

Initial release

2000

2014

1989

Current release

5.0.1, July 2024

SQL Server 2022, November 2022

License

Commercial or Open Source

commercial

Open Source

Apache License 2.0

commercial

restricted free version is available

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

Scala

C++

Server operating systems

hosted

Linux
Windows

Data scheme

yes

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.

Import/export of XML data possible

yes

Secondary indexes

yes

SQL

Support of SQL

yes

APIs and other access methods

.Net
JDBC
ODBC
WebSocket

.NET Client API
JDBC
ODBC
OLE DB

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

Supported programming languages

Java
Lua
Python
R

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

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

Server-side scripts

Stored procedures

user defined functions

PL/SQL, SQL PL

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

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

depending on storage layer

Sharding

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

Replication methods

Methods for redundantly storing data on multiple nodes

depending on storage layer

yes

yes, but depending on the SQL-Server Edition

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

depending on storage layer

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

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

depending on storage layer

yes

User concepts

Access control

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

yes

depending on the DBMS used for storage

fine grained access rights according to SQL-standard

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