DBMS > MonetDB vs. Quasardb vs. SAP HANA vs. SiteWhere

System Properties Comparison MonetDB vs. Quasardb vs. SAP HANA vs. SiteWhere

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Editorial information provided by DB-Engines

Name

Description

A relational database management system that stores data in columns

Distributed, high-performance timeseries database

In-memory, column based data store. Available as appliance or cloud service

M2M integration platform for persisting/querying time series data

Primary database model

Secondary database models

Document store
Spatial DBMS

Document store
Graph DBMS

with SAP Hana, Enterprise Edition
Spatial DBMS

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

Score	1.72
Rank	#141	Overall
	#64	Relational DBMS

Score	0.21
Rank	#322	Overall
	#29	Time Series DBMS

Score	44.27
Rank	#23	Overall
	#16	Relational DBMS

Score	0.06
Rank	#383	Overall
	#43	Time Series DBMS

Website

www.monetdb.org

quasar.ai

www.sap.com/products/hana.html

github.com/sitewhere/sitewhere

Technical documentation

www.monetdb.org/Documentation

doc.quasar.ai/master

help.sap.com/hana

sitewhere1.sitewhere.io/index.html

Developer

MonetDB BV

quasardb

SAP

SiteWhere

Initial release

2004

2009

2010

Current release

Dec2023 (11.49), December 2023

3.14.1, January 2024

2.0 SPS07 (April 4, 2023), April 2023

License

Commercial or Open Source

Open Source

Mozilla Public License 2.0

commercial

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

commercial

Open Source

Common Public Attribution License Version 1.0

Cloud-based only

Only available as a cloud service

also available as a cloud based service

DBaaS offerings (sponsored links)

Database as a Service

Providers of DBaaS offerings, please contact us to be listed.

Implementation language

C++

Java

Server operating systems

FreeBSD
Linux
OS X
Solaris
Windows

BSD
Linux
OS X
Windows

Appliance or cloud-service

Linux
OS X
Windows

Data scheme

yes

schema-free

yes

predefined scheme

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.

Secondary indexes

yes

with tags

yes

SQL

Support of SQL

yes

SQL 2003 with some extensions

SQL-like query language

yes

APIs and other access methods

JDBC
native C library

MAPI library (MonetDB application programming interface)
ODBC

HTTP API

JDBC
ODBC

HTTP REST

Supported programming languages

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

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

Server-side scripts

Stored procedures

yes, in SQL, C, R

SQLScript, R

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding via remote tables

Sharding

consistent hashing

yes

Sharding

based on HBase

Replication methods

Methods for redundantly storing data on multiple nodes

none

Source-replica replication available in experimental status

Source-replica replication with selectable replication factor

yes

selectable replication factor

based on HBase

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

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

User concepts

Access control

fine grained access rights according to SQL-standard

Cryptographically strong user authentication and audit trail

yes

Users with fine-grained authorization concept

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