DBMS > Microsoft Azure SQL Database vs. NSDb vs. RRDtool vs. Ultipa

System Properties Comparison Microsoft Azure SQL Database vs. NSDb vs. RRDtool vs. Ultipa

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Editorial information provided by DB-Engines

Name

Description

Database as a Service offering with high compatibility to Microsoft SQL Server

Scalable, High-performance Time Series DBMS designed for Real-time Analytics on top of Kubernetes

Industry standard data logging and graphing tool for time series data. RRD is an acronym for round-robin database.

The data is stored in a circular buffer, thus the system storage footprint remains constant over time.

High performance Graph DBMS supporting HTAP high availability cluster deployment

Primary database model

Relational DBMS

Time Series DBMS

Graph DBMS

Secondary database models

Document store
Graph DBMS
Spatial DBMS

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

Score	72.95
Rank	#16	Overall
	#11	Relational DBMS

Score	0.00
Rank	#385	Overall
	#40	Time Series DBMS

Score	1.70
Rank	#136	Overall
	#11	Time Series DBMS

Score	0.11
Rank	#338	Overall
	#32	Graph DBMS

Website

azure.microsoft.com/en-us/products/azure-sql/database

nsdb.io

oss.oetiker.ch/rrdtool

www.ultipa.com

Technical documentation

docs.microsoft.com/en-us/azure/azure-sql

nsdb.io/Architecture

oss.oetiker.ch/rrdtool/doc

www.ultipa.com/document

Developer

Microsoft

Tobias Oetiker

Ultipa

Initial release

2010

2017

1999

2019

Current release

V12

1.8.0, 2022

License

Commercial or Open Source

commercial

Open Source

Apache Version 2.0

Open Source

GPL V2 and FLOSS

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++

Java, Scala

Implementations in Java (e.g. RRD4J) and C# available

Server operating systems

hosted

Linux
macOS

HP-UX
Linux

Data scheme

yes

Typing

predefined data types such as float or date

yes

yes: int, bigint, decimal, string

Numeric data only

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

Exporting into and restoring from XML files possible

Secondary indexes

yes

all fields are automatically indexed

SQL

Support of SQL

yes

SQL-like query language

APIs and other access methods

ADO.NET
JDBC
ODBC

gRPC
HTTP REST
WebSocket

in-process shared library
Pipes

RESTful HTTP API

Supported programming languages

.Net
C#
Java
JavaScript (Node.js)
PHP
Python
Ruby

Java
Scala

with librrd library
C#

with a different implementation of RRDTool
Java

with a different implementation of RRDTool
JavaScript (Node.js)

with a different implementation of RRDTool
Lua
Perl
PHP

with a wrapper library
Python
Ruby

C++
Go
Java
JavaScript (Node.js)
Python

Server-side scripts

Stored procedures

Transact SQL

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

yes, with always 3 replicas available

none

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency

none

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

by using the rrdcached daemon

Durability

Support for making data persistent

yes

Using Apache Lucene

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

fine grained access rights according to SQL-standard

More information provided by the system vendor

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More resources

DB-Engines blog posts

PostgreSQL is the DBMS of the Year 2020
4 January 2021, Paul Andlinger, Matthias Gelbmann

Cloud-based DBMS's popularity grows at high rates
12 December 2019, Paul Andlinger

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7 February 2017, Matthias Gelbmann

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Time Series DBMS are the database category with the fastest increase in popularity
4 July 2016, Matthias Gelbmann

Time Series DBMS as a new trend?
1 June 2015, Paul Andlinger

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