DBMS > Microsoft Azure Data Explorer vs. NSDb vs. OpenQM

System Properties Comparison Microsoft Azure Data Explorer vs. NSDb vs. OpenQM

Please select another system to include it in the comparison.

Editorial information provided by DB-Engines

Name

Description

Fully managed big data interactive analytics platform

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

QpenQM is a high-performance, self-tuning, multi-value DBMS

Primary database model

Relational DBMS

column oriented

Time Series DBMS

Multivalue DBMS

Secondary database models

Document store

If a column is of type dynamic docs.microsoft.com/en-us/azure/kusto/query/scalar-data-types/dynamic then it's possible to add arbitrary JSON documents in this cell
Event Store

this is the general usage pattern at Microsoft. Billing, Logs, Telemetry events are stored in ADX and the state of an individual entity is defined by the arg_max(timestamps)
Spatial DBMS
Search engine

support for complex search expressions docs.microsoft.com/en-us/azure/kusto/query/parseoperator FTS, Geospatial docs.microsoft.com/en-us/azure/kusto/query/geo-point-to-geohash-function distributed search -> ADX acts as a distributed search engine
Time Series DBMS

see docs.microsoft.com/en-us/azure/data-explorer/time-series-analysis

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

Score	4.38
Rank	#77	Overall
	#41	Relational DBMS

Score	0.00
Rank	#383	Overall
	#41	Time Series DBMS

Score	0.27
Rank	#298	Overall
	#10	Multivalue DBMS

Website

azure.microsoft.com/services/data-explorer

nsdb.io

www.rocketsoftware.com/products/rocket-multivalue-application-development-platform/rocket-open-qm

Technical documentation

docs.microsoft.com/en-us/azure/data-explorer

nsdb.io/Architecture

Developer

Microsoft

Rocket Software, originally Martin Phillips

Initial release

2019

2017

1993

Current release

cloud service with continuous releases

3.4-12

License

Commercial or Open Source

commercial

Open Source

Apache Version 2.0

Open Source

GPLv2, extended commercial license available

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

Java, Scala

Server operating systems

hosted

Linux
macOS

AIX
FreeBSD
Linux
macOS
Raspberry Pi
Solaris
Windows

Data scheme

Fixed schema with schema-less datatypes (dynamic)

yes

with some exceptions

Typing

predefined data types such as float or date

yes

bool, datetime, dynamic, guid, int, long, real, string, timespan, double: docs.microsoft.com/en-us/azure/kusto/query/scalar-data-types

yes: int, bigint, decimal, string

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

Secondary indexes

all fields are automatically indexed

yes

SQL

Support of SQL

Kusto Query Language (KQL), SQL subset

SQL-like query language

APIs and other access methods

Microsoft SQL Server communication protocol (MS-TDS)
RESTful HTTP API

gRPC
HTTP REST
WebSocket

Supported programming languages

.Net
Go
Java
JavaScript (Node.js)
PowerShell
Python
R

Java
Scala

.Net
Basic
C
Java
Objective C
PHP
Python

Server-side scripts

Stored procedures

Yes, possible languages: KQL, Python, R

yes

Triggers

yes

see docs.microsoft.com/en-us/azure/kusto/management/updatepolicy

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

Implicit feature of the cloud service

Sharding

yes

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Implicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

Spark connector (open source): github.com/Azure/azure-kusto-spark

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency
Immediate Consistency

Eventual Consistency

Immediate Consistency

Foreign keys

Referential integrity

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

Using Apache Lucene

yes

In-memory capabilities

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

User concepts

Access control

Azure Active Directory Authentication

Access rights can be defined down to the item level

More information provided by the system vendor

We invite representatives of system vendors to contact us for updating and extending the system information,
and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.

Related products and services

We invite representatives of vendors of related products to contact us for presenting information about their offerings here.

More resources

Recent citations in the news

Azure Data Explorer: Log and telemetry analytics benchmark
16 August 2022, Microsoft

Providing modern data transfer and storage service at Microsoft with Microsoft Azure - Inside Track Blog
13 July 2023, Microsoft

Controlling costs in Azure Data Explorer using down-sampling and aggregation
11 February 2019, Microsoft

Individually great, collectively unmatched: Announcing updates to 3 great Azure Data Services
7 February 2019, Microsoft

Analytics in Azure is up to 14x faster and costs 94% less than other cloud providers. Why go anywhere else?
7 February 2019, Microsoft

provided by Google News

Share this page