DBMS > Fauna vs. Microsoft SQL Server vs. Qdrant vs. Snowflake

System Properties Comparison Fauna vs. Microsoft SQL Server vs. Qdrant vs. Snowflake

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Editorial information provided by DB-Engines

Name

Description

Fauna provides a web-native interface, with support for GraphQL and custom business logic that integrates seamlessly with the rest of the serverless ecosystem. The underlying globally distributed storage and compute platform is fast, consistent, and reliable, with a modern security infrastructure.

Microsofts flagship relational DBMS

A high-performance vector database with neural network or semantic-based matching

Cloud-based data warehousing service for structured and semi-structured data

Primary database model

Document store
Graph DBMS
Relational DBMS
Time Series DBMS

Relational DBMS

Vector DBMS

Relational DBMS

Secondary database models

Document store
Graph DBMS
Spatial DBMS

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

Score	1.52
Rank	#153	Overall
	#26	Document stores
	#14	Graph DBMS
	#71	Relational DBMS
	#13	Time Series DBMS

Score	824.29
Rank	#3	Overall
	#3	Relational DBMS

Score	1.16
Rank	#175	Overall
	#6	Vector DBMS

Score	121.33
Rank	#9	Overall
	#6	Relational DBMS

Website

fauna.com

www.microsoft.com/en-us/sql-server

github.com/qdrant/qdrant
qdrant.tech

www.snowflake.com

Technical documentation

docs.fauna.com

learn.microsoft.com/en-US/sql/sql-server

qdrant.tech/documentation

docs.snowflake.net/manuals/index.html

Developer

Fauna, Inc.

Microsoft

Qdrant

Snowflake Computing Inc.

Initial release

2014

1989

2021

2014

Current release

SQL Server 2022, November 2022

License

Commercial or Open Source

commercial

restricted free version is available

Open Source

Apache Version 2.0

commercial

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

Scala

C++

Rust

Server operating systems

hosted

Linux
Windows

Docker
Linux
macOS
Windows

hosted

Data scheme

schema-free

yes

schema-free

yes

support of semi-structured data formats (JSON, XML, Avro)

Typing

predefined data types such as float or date

yes

Numbers, Strings, Geo, Boolean

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

Keywords, numberic ranges, geo, full-text

SQL

Support of SQL

yes

APIs and other access methods

RESTful HTTP API

ADO.NET
JDBC
ODBC
OLE DB
Tabular Data Stream (TDS)

gRPC
OpenAPI 3.0
RESTful HTTP/JSON API

OpenAPI 3.0

CLI Client
JDBC
ODBC

Supported programming languages

C#
Go
Java
JavaScript
Python
Ruby
Scala
Swift

C#
C++
Delphi
Go
Java
JavaScript (Node.js)
PHP
Python
R
Ruby
Visual Basic

.Net
Go
Java
JavaScript (Node.js)
Python
Rust

JavaScript (Node.js)
Python

Server-side scripts

Stored procedures

user defined functions

Transact SQL, .NET languages, R, Python and (with SQL Server 2019) Java

user defined functions

Triggers

yes

similar concept for controling cloud resources

Partitioning methods

Methods for storing different data on different nodes

horizontal partitioning

consistent hashing

tables can be distributed across several files (horizontal partitioning); sharding through federation

Sharding

yes

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication

yes, but depending on the SQL-Server Edition

Collection-level replication

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency, tunable 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

In-memory capabilities

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

yes

User concepts

Access control

Identity management, authentication, and access control

fine grained access rights according to SQL-standard

Key-based authentication

Users with fine-grained authorization concept, user roles and pluggable authentication

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