DBMS > Fauna vs. Quasardb vs. Snowflake vs. TigerGraph

System Properties Comparison Fauna vs. Quasardb vs. Snowflake vs. TigerGraph

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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.

Distributed, high-performance timeseries database

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

A complete, distributed, parallel graph computing platform supporting web-scale data analytics in real-time

Primary database model

Document store
Graph DBMS
Relational DBMS
Time Series DBMS

Time Series DBMS

Relational DBMS

Graph DBMS

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

Score	1.55
Rank	#151	Overall
	#26	Document stores
	#14	Graph DBMS
	#71	Relational DBMS
	#13	Time Series DBMS

Score	0.21
Rank	#322	Overall
	#29	Time Series DBMS

Score	130.36
Rank	#8	Overall
	#5	Relational DBMS

Score	1.80
Rank	#138	Overall
	#13	Graph DBMS

Website

Technical documentation

docs.fauna.com

doc.quasar.ai/master

docs.snowflake.net/manuals/index.html

docs.tigergraph.com

Developer

Fauna, Inc.

quasardb

Snowflake Computing Inc.

Initial release

2014

2009

2014

2017

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

commercial

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++

Server operating systems

hosted

BSD
Linux
OS X
Windows

hosted

Linux

Data scheme

schema-free

yes

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

yes

Typing

predefined data types such as float or date

yes

integer and binary

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

with tags

SQL

Support of SQL

SQL-like query language

yes

SQL-like query language (GSQL)

APIs and other access methods

RESTful HTTP API

HTTP API

CLI Client
JDBC
ODBC

GSQL (TigerGraph Query Language)
Kafka
RESTful HTTP/JSON API

Supported programming languages

C#
Go
Java
JavaScript
Python
Ruby
Scala
Swift

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

JavaScript (Node.js)
Python

C++
Java

Server-side scripts

Stored procedures

user defined functions

yes

Triggers

similar concept for controling cloud resources

Partitioning methods

Methods for storing different data on different nodes

horizontal partitioning

consistent hashing

Sharding

consistent hashing

yes

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication

Source-replica replication with selectable replication factor

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

with Hadoop integration

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Foreign keys

Referential integrity

yes

Relationships in graphs

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

by using LevelDB

yes

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

Cryptographically strong user authentication and audit trail

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

Role-based access control

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