DBMS > Amazon Redshift vs. Apache IoTDB vs. BoltDB vs. InfluxDB

System Properties Comparison Amazon Redshift vs. Apache IoTDB vs. BoltDB vs. InfluxDB

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Editorial information provided by DB-Engines

Name

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

An embedded key-value store for Go.

DBMS for storing time series, events and metrics

Primary database model

Secondary database models

Spatial DBMS

with GEO package

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

Score	15.25
Rank	#38	Overall
	#23	Relational DBMS

Score	1.31
Rank	#159	Overall
	#14	Time Series DBMS

Score	0.70
Rank	#225	Overall
	#31	Key-value stores

Score	22.12
Rank	#28	Overall
	#1	Time Series DBMS

Website

aws.amazon.com/redshift

iotdb.apache.org

github.com/boltdb/bolt

www.influxdata.com/products/influxdb-overview

Technical documentation

docs.aws.amazon.com/redshift

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

docs.influxdata.com/influxdb

Developer

Amazon (based on PostgreSQL)

Apache Software Foundation

Initial release

2012

2018

2013

Current release

1.1.0, April 2023

2.7.6, April 2024

License

Commercial or Open Source

commercial

Open Source

Apache Version 2.0

Open Source

MIT License

Open Source

MIT-License; commercial enterprise version available

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

Java

Server operating systems

hosted

All OS with a Java VM (>= 1.8)

BSD
Linux
OS X
Solaris
Windows

Linux
OS X

through Homebrew

Data scheme

yes

schema-free

Typing

predefined data types such as float or date

yes

Numeric data and Strings

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

APIs and other access methods

JDBC
ODBC

JDBC
Native API

HTTP API
JSON over UDP

Supported programming languages

All languages supporting JDBC/ODBC

C
C#
C++
Go
Java
Python
Scala

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

Server-side scripts

Stored procedures

user defined functions

in Python

yes

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

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

none

Sharding

in enterprise version only

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

selectable replication factor

in enterprise version only

MapReduce

Offers an API for user-defined Map/Reduce methods

Integration with Hadoop and Spark

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

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

yes

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

Depending on used storage engine

User concepts

Access control

fine grained access rights according to SQL-standard

yes

simple rights management via user accounts

More information provided by the system vendor

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