DBMS > Fauna vs. FeatureBase vs. Snowflake vs. Tkrzw

System Properties Comparison Fauna vs. FeatureBase vs. Snowflake vs. Tkrzw

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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.

Real-time database platform that powers real-time analytics and machine learning applications by simultaneously executing low-latency, high-throughput, and highly concurrent workloads.

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

A concept of libraries, allowing an application program to store and query key-value pairs in a file. Successor of Tokyo Cabinet and Kyoto Cabinet

Primary database model

Document store
Graph DBMS
Relational DBMS
Time Series DBMS

Relational DBMS

Key-value store

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	0.22
Rank	#309	Overall
	#139	Relational DBMS

Score	121.33
Rank	#9	Overall
	#6	Relational DBMS

Score	0.00
Rank	#383	Overall
	#60	Key-value stores

Website

Technical documentation

docs.fauna.com

docs.featurebase.com

docs.snowflake.net/manuals/index.html

Developer

Fauna, Inc.

Molecula and Pilosa Open Source Contributors

Snowflake Computing Inc.

Mikio Hirabayashi

Initial release

2014

2017

2014

2020

Current release

2022, May 2022

0.9.3, August 2020

License

Commercial or Open Source

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

Scala

C++

Server operating systems

hosted

Linux
macOS

hosted

Linux
macOS

Data scheme

schema-free

yes

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

schema-free

Typing

predefined data types such as float or date

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

SQL

Support of SQL

SQL queries

yes

APIs and other access methods

RESTful HTTP API

gRPC
JDBC
Kafka Connector
ODBC

CLI Client
JDBC
ODBC

Supported programming languages

C#
Go
Java
JavaScript
Python
Ruby
Scala
Swift

Java
Python

JavaScript (Node.js)
Python

C++
Java
Python
Ruby

Server-side scripts

Stored procedures

user defined functions

Triggers

similar concept for controling cloud resources

Partitioning methods

Methods for storing different data on different nodes

horizontal partitioning

consistent hashing

Sharding

yes

none

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication

yes

none

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

yes

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

yes, using Linux fsync

yes

In-memory capabilities

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

yes

using specific database classes

User concepts

Access control

Identity management, authentication, and access control

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

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