DBMS > Amazon Redshift vs. Apache IoTDB vs. FatDB vs. FoundationDB

System Properties Comparison Amazon Redshift vs. Apache IoTDB vs. FatDB vs. FoundationDB

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Editorial information provided by DB-Engines

Name

FatDB/FatCloud has ceased operations as a company with February 2014. FatDB is discontinued and excluded from the ranking.

Created as commercial project in 2013, FoundationDB has been acquired by Apple in March 2015 and was withdrawn from the market. As a consequence, the product was removed from the DB-Engines ranking. In April 2018, Apple open-sourced FoundationDB and it therefore reappears in the ranking.

Description

Large scale data warehouse service for use with business intelligence tools

An IoT native database with high performance for data management and analysis, deployable on the edge and the cloud and integrated with Hadoop, Spark and Flink

A .NET NoSQL DBMS that can integrate with and extend SQL Server.

Ordered key-value store. Core features are complimented by layers.

Primary database model

Relational DBMS

Time Series DBMS

Document store
Key-value store

Document store

supported via specific layer
Key-value store
Relational DBMS

supported via specific SQL-layer

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

Score	17.94
Rank	#34	Overall
	#21	Relational DBMS

Score	1.18
Rank	#173	Overall
	#15	Time Series DBMS

Score	1.03
Rank	#190	Overall
	#31	Document stores
	#28	Key-value stores
	#89	Relational DBMS

Website

aws.amazon.com/redshift

iotdb.apache.org

github.com/apple/foundationdb

Technical documentation

docs.aws.amazon.com/redshift

iotdb.apache.org/UserGuide/Master/QuickStart/QuickStart.html

apple.github.io/foundationdb

Developer

Amazon (based on PostgreSQL)

Apache Software Foundation

FatCloud

FoundationDB

Initial release

2012

2018

2012

2013

Current release

1.1.0, April 2023

6.2.28, November 2020

License

Commercial or Open Source

commercial

Open Source

Apache Version 2.0

commercial

Open Source

Apache 2.0

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

Java

C++

Server operating systems

hosted

All OS with a Java VM (>= 1.8)

Windows

Linux
OS X
Windows

Data scheme

yes

schema-free

some layers support schemas

Typing

predefined data types such as float or date

yes

some layers support typing

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

Via inetgration in SQL Server

supported in specific SQL layer only

APIs and other access methods

JDBC
ODBC

JDBC
Native API

.NET Client API
LINQ
RESTful HTTP API
RPC
Windows WCF Bindings

Supported programming languages

All languages supporting JDBC/ODBC

C
C#
C++
Go
Java
Python
Scala

.Net
C
C++
Go
Java
JavaScript

Node.js
PHP
Python
Ruby
Swift

Server-side scripts

Stored procedures

user defined functions

in Python

yes

via applications

in SQL-layer only

Triggers

yes

via applications

Partitioning methods

Methods for storing different data on different nodes

Sharding

horizontal partitioning (by time range) + vertical partitioning (by deviceId)

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

yes

selectable replication methods; using Raft/IoTConsensus algorithm to ensure strong/eventual data consistency among multiple replicas

selectable replication factor

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

Integration with Hadoop and Spark

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency
Strong Consistency with Raft

Eventual Consistency
Immediate Consistency

Linearizable consistency

Foreign keys

Referential integrity

yes

informational only, not enforced by the system

in SQL-layer only

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

fine grained access rights according to SQL-standard

yes

Can implement custom security layer via applications

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