DBMS > Amazon Redshift vs. Apache Drill vs. Apache IoTDB vs. RRDtool

System Properties Comparison Amazon Redshift vs. Apache Drill vs. Apache IoTDB vs. RRDtool

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Editorial information provided by DB-Engines

Name

Description

Large scale data warehouse service for use with business intelligence tools

Schema-free SQL Query Engine for Hadoop, NoSQL and Cloud Storage

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

Industry standard data logging and graphing tool for time series data. RRD is an acronym for round-robin database.

The data is stored in a circular buffer, thus the system storage footprint remains constant over time.

Primary database model

Relational DBMS

Document store
Relational DBMS

Time Series DBMS

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

Score	16.88
Rank	#35	Overall
	#22	Relational DBMS

Score	2.02
Rank	#124	Overall
	#22	Document stores
	#59	Relational DBMS

Score	1.31
Rank	#164	Overall
	#14	Time Series DBMS

Score	1.90
Rank	#132	Overall
	#11	Time Series DBMS

Website

aws.amazon.com/redshift

drill.apache.org

iotdb.apache.org

oss.oetiker.ch/rrdtool

Technical documentation

docs.aws.amazon.com/redshift

drill.apache.org/docs

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

oss.oetiker.ch/rrdtool/doc

Developer

Amazon (based on PostgreSQL)

Apache Software Foundation

Tobias Oetiker

Initial release

2012

2018

1999

Current release

1.20.3, January 2023

1.1.0, April 2023

1.8.0, 2022

License

Commercial or Open Source

commercial

Open Source

Apache Version 2

Open Source

Apache Version 2.0

Open Source

GPL V2 and FLOSS

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

Implementations in Java (e.g. RRD4J) and C# available

Server operating systems

hosted

Linux
OS X
Windows

All OS with a Java VM (>= 1.8)

HP-UX
Linux

Data scheme

yes

schema-free

yes

Typing

predefined data types such as float or date

yes

Numeric data only

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.

Exporting into and restoring from XML files possible

Secondary indexes

restricted

yes

SQL

Support of SQL

yes

does not fully support an SQL-standard

SQL SELECT statement is SQL:2003 compliant

SQL-like query language

APIs and other access methods

JDBC
ODBC

JDBC
ODBC
RESTful HTTP API

JDBC
Native API

in-process shared library
Pipes

Supported programming languages

All languages supporting JDBC/ODBC

C++

C
C#
C++
Go
Java
Python
Scala

with librrd library
C#

with a different implementation of RRDTool
Java

with a different implementation of RRDTool
JavaScript (Node.js)

with a different implementation of RRDTool
Lua
Perl
PHP

with a wrapper library
Python
Ruby

Server-side scripts

Stored procedures

user defined functions

in Python

user defined functions

yes

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

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

none

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

none

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Integration with Hadoop and Spark

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

none

Eventual Consistency
Strong Consistency with Raft

none

Foreign keys

Referential integrity

yes

informational only, not enforced by the system

Transaction concepts

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

ACID

Concurrency

Support for concurrent manipulation of data

yes

by using the rrdcached daemon

Durability

Support for making data persistent

yes

Depending on the underlying data source

yes

In-memory capabilities

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

yes

Depending on the underlying data source

yes

User concepts

Access control

fine grained access rights according to SQL-standard

Depending on the underlying data source

yes

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