DBMS > Fauna vs. Linter vs. Microsoft Azure Cosmos DB vs. Quasardb

System Properties Comparison Fauna vs. Linter vs. Microsoft Azure Cosmos DB vs. Quasardb

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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.

RDBMS for high security requirements

Globally distributed, horizontally scalable, multi-model database service

Distributed, high-performance timeseries database

Primary database model

Document store
Graph DBMS
Relational DBMS
Time Series DBMS

Relational DBMS

Document store
Graph DBMS
Key-value store
Wide column store

Time Series DBMS

Secondary database models

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	0.09
Rank	#346	Overall
	#152	Relational DBMS

Score	29.04
Rank	#27	Overall
	#4	Document stores
	#2	Graph DBMS
	#3	Key-value stores
	#3	Wide column stores

Score	0.14
Rank	#332	Overall
	#29	Time Series DBMS

Website

fauna.com

linter.ru

azure.microsoft.com/services/cosmos-db

quasar.ai

Technical documentation

docs.fauna.com

learn.microsoft.com/azure/cosmos-db

doc.quasar.ai/master

Developer

Fauna, Inc.

relex.ru

Microsoft

quasardb

Initial release

2014

1990

2014

2009

Current release

3.14.1, January 2024

License

Commercial or Open Source

commercial

Free community edition, Non-profit organizations and non-commercial usage are eligible for free licenses

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

Scala

C and C++

C++

Server operating systems

hosted

AIX
Android
BSD
HP Open VMS
iOS
Linux
OS X
VxWorks
Windows

hosted

BSD
Linux
OS X
Windows

Data scheme

schema-free

yes

schema-free

Typing

predefined data types such as float or date

yes

JSON types

yes

integer and binary

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.

Secondary indexes

yes

All properties auto-indexed by default

yes

with tags

SQL

Support of SQL

yes

SQL-like query language

APIs and other access methods

RESTful HTTP API

ADO.NET
JDBC
LINQ
ODBC
OLE DB
Oracle Call Interface (OCI)

DocumentDB API
Graph API (Gremlin)
MongoDB API
RESTful HTTP API
Table API

HTTP API

Supported programming languages

C#
Go
Java
JavaScript
Python
Ruby
Scala
Swift

C
C#
C++
Java
Perl
PHP
Python
Qt
Ruby
Tcl

.Net
C#
Java
JavaScript
JavaScript (Node.js)
MongoDB client drivers written for various programming languages
Python

.Net
C
C#
C++
Go
Java
JavaScript (Node.js)
PHP
Python
R

Server-side scripts

Stored procedures

user defined functions

yes

proprietary syntax with the possibility to convert from PL/SQL

JavaScript

Triggers

yes

JavaScript

Partitioning methods

Methods for storing different data on different nodes

horizontal partitioning

consistent hashing

none

Sharding

Implicit feature of the cloud service

Sharding

consistent hashing

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication

Source-replica replication

yes

Implicit feature of the cloud service

Source-replica replication with selectable replication factor

MapReduce

Offers an API for user-defined Map/Reduce methods

with Hadoop integration

Integration with Hadoop/HDInsight on Azure*

with Hadoop integration

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Bounded Staleness
Consistent Prefix
Eventual Consistency
Immediate Consistency

Consistency level configurable on request level
Session Consistency

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

Multi-item ACID transactions with snapshot isolation within a partition

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

by using LevelDB

In-memory capabilities

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

yes

Transient mode

User concepts

Access control

Identity management, authentication, and access control

fine grained access rights according to SQL-standard

Access rights can be defined down to the item level

Cryptographically strong user authentication and audit trail

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