DBMS > FatDB vs. Microsoft Azure SQL Database vs. NSDb vs. OpenMLDB

System Properties Comparison FatDB vs. Microsoft Azure SQL Database vs. NSDb vs. OpenMLDB

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Editorial information provided by DB-Engines

Name

FatDB/FatCloud has ceased operations as a company with February 2014. FatDB is discontinued and excluded from the ranking.

Description

A .NET NoSQL DBMS that can integrate with and extend SQL Server.

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

An open-source machine learning database that provides a feature platform for training and inference

Primary database model

Document store
Key-value store

Relational DBMS

Time Series DBMS

Secondary database models

Document store
Graph DBMS
Spatial DBMS

Relational 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	0.11
Rank	#339	Overall
	#30	Time Series DBMS

Website

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

nsdb.io

openmldb.ai

Technical documentation

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

nsdb.io/Architecture

openmldb.ai/docs/zh/main

Developer

FatCloud

Microsoft

4 Paradigm Inc.

Initial release

2012

2010

2017

2020

Current release

V12

2024-2 February 2024

License

Commercial or Open Source

commercial

Open Source

Apache Version 2.0

Open Source

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

C++, Java, Scala

Server operating systems

Windows

hosted

Linux
macOS

Linux

Data scheme

schema-free

yes

Fixed schema

Typing

predefined data types such as float or date

yes

yes: int, bigint, decimal, string

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

Secondary indexes

yes

all fields are automatically indexed

yes

SQL

Support of SQL

Via inetgration in SQL Server

yes

SQL-like query language

yes

APIs and other access methods

.NET Client API
LINQ
RESTful HTTP API
RPC
Windows WCF Bindings

ADO.NET
JDBC
ODBC

gRPC
HTTP REST
WebSocket

JDBC
SQLAlchemy

Supported programming languages

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

Java
Scala

C++
Go
Java
Python
Scala

Server-side scripts

Stored procedures

yes

via applications

Transact SQL

Triggers

yes

via applications

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

horizontal partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor

yes, with always 3 replicas available

Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency
Immediate Consistency

Immediate Consistency

Eventual Consistency

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

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

Can implement custom security layer via applications

fine grained access rights according to SQL-standard

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