DBMS > Amazon DynamoDB vs. Apache IoTDB vs. EventStoreDB vs. Hazelcast vs. Riak TS

System Properties Comparison Amazon DynamoDB vs. Apache IoTDB vs. EventStoreDB vs. Hazelcast vs. Riak TS

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.

A widely adopted in-memory data grid

Riak TS is a distributed NoSQL database optimized for time series data and based on Riak KV

Primary database model

Document store
Key-value store

Secondary database models

Document store

JSON support with IMDG 3.12

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

Score	70.06
Rank	#17	Overall
	#3	Document stores
	#2	Key-value stores

Score	1.31
Rank	#159	Overall
	#14	Time Series DBMS

Score	1.07
Rank	#181	Overall
	#1	Event Stores

Score	5.72
Rank	#59	Overall
	#6	Key-value stores

Score	0.17
Rank	#318	Overall
	#27	Time Series DBMS

Website

aws.amazon.com/dynamodb

iotdb.apache.org

www.eventstore.com

hazelcast.com

Technical documentation

docs.aws.amazon.com/dynamodb

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

developers.eventstore.com

hazelcast.org/imdg/docs

www.tiot.jp/riak-docs/riak/ts/latest

Developer

Amazon

Apache Software Foundation

Event Store Limited

Hazelcast

Open Source, formerly Basho Technologies

Initial release

2012

2018

2012

2008

2015

Current release

1.1.0, April 2023

21.2, February 2021

5.3.6, November 2023

3.0.0, September 2022

License

Commercial or Open Source

commercial

free tier for a limited amount of database operations

Open Source

Apache Version 2.0

Open Source

Apache Version 2; commercial licenses available

Open Source

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

Erlang

Server operating systems

hosted

All OS with a Java VM (>= 1.8)

Linux
Windows

All OS with a Java VM

Linux
OS X

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

the object must implement a serialization strategy

Secondary indexes

yes

restricted

SQL

Support of SQL

SQL-like query language

yes, limited

APIs and other access methods

RESTful HTTP API

JDBC
Native API

JCache
JPA
Memcached protocol
RESTful HTTP API

HTTP API
Native Erlang Interface

Supported programming languages

.Net
ColdFusion
Erlang
Groovy
Java
JavaScript
Perl
PHP
Python
Ruby

C
C#
C++
Go
Java
Python
Scala

.Net
C#
C++
Clojure
Go
Java
JavaScript (Node.js)
Python
Scala

unofficial client library
C#
C++

unofficial client library
Clojure

unofficial client library
Dart

unofficial client library
Erlang
Go

unofficial client library
Groovy

unofficial client library
Haskell

unofficial client library
Java
JavaScript

unofficial client library
Lisp

unofficial client library
Perl

unofficial client library
PHP
Python
Ruby
Scala

unofficial client library
Smalltalk

unofficial client library

Server-side scripts

Stored procedures

yes

Event Listeners, Executor Services

Erlang

Triggers

yes

by integration with AWS Lambda

yes

Events

yes

pre-commit hooks and post-commit hooks

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

yes

Replicated Map

selectable replication factor

MapReduce

Offers an API for user-defined Map/Reduce methods

may be implemented via Amazon Elastic MapReduce (Amazon EMR)

Integration with Hadoop and Spark

yes

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 or Eventual Consistency selectable by user

Raft Consensus Algorithm

Eventual Consistency

Foreign keys

Referential integrity

links between datasets can be stored

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

one or two-phase-commit; repeatable reads; read commited

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

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

yes

Role-based access control

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