DBMS > Amazon Redshift vs. Fauna vs. InfluxDB vs. PlanetScale

System Properties Comparison Amazon Redshift vs. Fauna vs. InfluxDB vs. PlanetScale

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Editorial information provided by DB-Engines

Name

Description

Large scale data warehouse service for use with business intelligence tools

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.

DBMS for storing time series, events and metrics

Scalable, distributed, serverless MySQL database platform built on top of Vitess

Primary database model

Relational DBMS

Document store
Graph DBMS
Relational DBMS
Time Series DBMS

Time Series DBMS

Relational DBMS

Secondary database models

Spatial DBMS

with GEO package

Document store
Spatial DBMS

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

Score	16.88
Rank	#35	Overall
	#22	Relational DBMS

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

Score	24.39
Rank	#28	Overall
	#1	Time Series DBMS

Score	1.49
Rank	#155	Overall
	#72	Relational DBMS

Website

aws.amazon.com/redshift

fauna.com

www.influxdata.com/products/influxdb-overview

planetscale.com

Technical documentation

docs.aws.amazon.com/redshift

docs.fauna.com

docs.influxdata.com/influxdb

planetscale.com/docs

Developer

Amazon (based on PostgreSQL)

Fauna, Inc.

PlanetScale

Initial release

2012

2014

2013

2020

Current release

2.7.6, April 2024

License

Commercial or Open Source

commercial

Open Source

MIT-License; commercial enterprise version available

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

Server operating systems

hosted

Linux
OS X

through Homebrew

Docker
Linux
macOS

Data scheme

yes

schema-free

yes

Typing

predefined data types such as float or date

yes

Numeric data and Strings

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.

Secondary indexes

restricted

yes

SQL

Support of SQL

yes

does not fully support an SQL-standard

SQL-like query language

yes

with proprietary extensions

APIs and other access methods

JDBC
ODBC

RESTful HTTP API

HTTP API
JSON over UDP

ADO.NET
JDBC
MySQL protocol
ODBC

Supported programming languages

All languages supporting JDBC/ODBC

C#
Go
Java
JavaScript
Python
Ruby
Scala
Swift

.Net
Clojure
Erlang
Go
Haskell
Java
JavaScript
JavaScript (Node.js)
Lisp
Perl
PHP
Python
R
Ruby
Rust
Scala

Ada
C
C#
C++
D
Delphi
Eiffel
Erlang
Haskell
Java
JavaScript (Node.js)
Objective-C
OCaml
Perl
PHP
Python
Ruby
Scheme
Tcl

Server-side scripts

Stored procedures

user defined functions

in Python

user defined functions

yes

proprietary syntax

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

horizontal partitioning

consistent hashing

Sharding

in enterprise version only

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Multi-source replication

selectable replication factor

in enterprise version only

Multi-source replication
Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency across shards
Immediate Consistency within a shard

Foreign keys

Referential integrity

yes

informational only, not enforced by the system

yes

not for MyISAM storage engine

Transaction concepts

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

ACID

ACID at shard level

Concurrency

Support for concurrent manipulation of data

yes

table locks or row locks depending on storage engine

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

Depending on used storage engine

yes

User concepts

Access control

fine grained access rights according to SQL-standard

Identity management, authentication, and access control

simple rights management via user accounts

Users with fine-grained authorization concept

no user groups or roles

More information provided by the system vendor

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