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

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

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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

An open-source, elastic, and workload-aware cloud data warehouse designed to meet businesses' massive-scale analytics needs at low cost and with low complexity

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

Primary database model

Relational DBMS

Document store
Key-value store

Relational DBMS

Time Series DBMS

Secondary database models

Document store
Graph DBMS
Spatial DBMS

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

Score	0.34
Rank	#283	Overall
	#130	Relational DBMS

Score	76.78
Rank	#16	Overall
	#11	Relational DBMS

Score	0.08
Rank	#369	Overall
	#40	Time Series DBMS

Website

github.com/datafuselabs/databend
www.databend.com

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

nsdb.io

Technical documentation

docs.databend.com

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

nsdb.io/Architecture

Developer

Databend Labs

FatCloud

Microsoft

Initial release

2021

2012

2010

2017

Current release

1.0.59, April 2023

V12

License

Commercial or Open Source

Open Source

Apache Version 2.0

commercial

Open Source

Apache Version 2.0

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

Rust

C++

Java, Scala

Server operating systems

hosted
Linux
macOS

Windows

hosted

Linux
macOS

Data scheme

yes

schema-free

yes

Typing

predefined data types such as float or date

yes

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

yes

all fields are automatically indexed

SQL

Support of SQL

yes

Via inetgration in SQL Server

yes

SQL-like query language

APIs and other access methods

CLI Client
JDBC
RESTful HTTP API

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

ADO.NET
JDBC
ODBC

gRPC
HTTP REST
WebSocket

Supported programming languages

Go
Java
JavaScript (Node.js)
Python
Rust

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

Java
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

none

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

none

selectable replication factor

yes, with always 3 replicas available

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency
Immediate Consistency

Immediate Consistency

Eventual Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

Support to ensure data integrity after non-atomic manipulations of data

yes

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

Using Apache Lucene

User concepts

Access control

Users with fine-grained authorization concept, user roles

Can implement custom security layer via applications

fine grained access rights according to SQL-standard

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