DBMS > Amazon DynamoDB vs. Apache IoTDB vs. EventStoreDB vs. MySQL vs. SwayDB

System Properties Comparison Amazon DynamoDB vs. Apache IoTDB vs. EventStoreDB vs. MySQL vs. SwayDB

Editorial information provided by DB-Engines

Name

Description

Hosted, scalable database service by Amazon with the data stored in Amazons cloud

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

Industrial-strength, open-source database solution built from the ground up for event sourcing.

Widely used open source RDBMS

An embeddable, non-blocking, type-safe key-value store for single or multiple disks and in-memory storage

Primary database model

Document store
Key-value store

Time Series DBMS

Event Store

Relational DBMS

Key/Value like access via memcached API

Key-value store

Secondary database models

Document store
Spatial DBMS

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

Score	74.07
Rank	#17	Overall
	#3	Document stores
	#2	Key-value stores

Score	1.18
Rank	#173	Overall
	#15	Time Series DBMS

Score	1.10
Rank	#179	Overall
	#1	Event Stores

Score	1083.74
Rank	#2	Overall
	#2	Relational DBMS

Score	0.00
Rank	#382	Overall
	#59	Key-value stores

Website

aws.amazon.com/dynamodb

Technical documentation

docs.aws.amazon.com/dynamodb

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

developers.eventstore.com

dev.mysql.com/doc

Developer

Amazon

Apache Software Foundation

Event Store Limited

Oracle

since 2010, originally MySQL AB, then Sun

Simer Plaha

Initial release

2012

2018

2012

1995

2018

Current release

1.1.0, April 2023

21.2, February 2021

8.4.0, April 2024

License

Commercial or Open Source

commercial

free tier for a limited amount of database operations

Open Source

Apache Version 2.0

Open Source

GPL version 2. Commercial licenses with extended functionallity are available

Open Source

GNU Affero GPL V3.0

Cloud-based only

Only available as a cloud service

yes

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Implementation language

Java

C and C++

Scala

Server operating systems

hosted

All OS with a Java VM (>= 1.8)

Linux
Windows

FreeBSD
Linux
OS X
Solaris
Windows

Data scheme

schema-free

yes

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-like query language

yes

with proprietary extensions

APIs and other access methods

RESTful HTTP API

JDBC
Native API

ADO.NET
JDBC
ODBC
Proprietary native API

Supported programming languages

.Net
ColdFusion
Erlang
Groovy
Java
JavaScript
Perl
PHP
Python
Ruby

C
C#
C++
Go
Java
Python
Scala

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

Java
Kotlin
Scala

Server-side scripts

Stored procedures

yes

proprietary syntax

Triggers

yes

by integration with AWS Lambda

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

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

horizontal partitioning, sharding with MySQL Cluster or MySQL Fabric

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

Multi-source replication
Source-replica replication

none

MapReduce

Offers an API for user-defined Map/Reduce methods

may be implemented via Amazon Elastic MapReduce (Amazon EMR)

Integration with Hadoop and Spark

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency
Immediate Consistency

can be specified for read operations

Eventual Consistency
Strong Consistency with Raft

Immediate Consistency

Foreign keys

Referential integrity

yes

not for MyISAM storage engine

Transaction concepts

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

ACID

ACID across one or more tables within a single AWS account and region

ACID

not for MyISAM storage engine

Atomic execution of operations

Concurrency

Support for concurrent manipulation of data

yes

table locks or row locks depending on storage engine

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

Access rights for users and roles can be defined via the AWS Identity and Access Management (IAM)

yes

Users with fine-grained authorization concept

no user groups or roles

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