DBMS > Amazon DynamoDB vs. etcd vs. IBM Db2 Event Store vs. SiteWhere

System Properties Comparison Amazon DynamoDB vs. etcd vs. IBM Db2 Event Store vs. SiteWhere

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Editorial information provided by DB-Engines

Name

Description

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

A distributed reliable key-value store

Distributed Event Store optimized for Internet of Things use cases

M2M integration platform for persisting/querying time series data

Primary database model

Document store
Key-value store

Key-value store

Event Store
Time Series DBMS

Time Series DBMS

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	7.05
Rank	#53	Overall
	#5	Key-value stores

Score	0.18
Rank	#315	Overall
	#2	Event Stores
	#26	Time Series DBMS

Score	0.07
Rank	#347	Overall
	#33	Time Series DBMS

Website

aws.amazon.com/dynamodb

etcd.io
github.com/etcd-io/etcd

www.ibm.com/products/db2-event-store

github.com/sitewhere/sitewhere

Technical documentation

docs.aws.amazon.com/dynamodb

etcd.io/docs
github.com/etcd-io/etcd/tree/master/Documentation

www.ibm.com/docs/en/db2-event-store

sitewhere1.sitewhere.io/index.html

Developer

Amazon

IBM

SiteWhere

Initial release

2012

2017

2010

Current release

3.4, August 2019

2.0

License

Commercial or Open Source

commercial

free tier for a limited amount of database operations

Open Source

Apache Version 2.0

commercial

free developer edition available

Open Source

Common Public Attribution License Version 1.0

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

C and C++

Java

Server operating systems

hosted

FreeBSD
Linux
Windows

experimental

Linux

Linux, macOS, Windows for the developer addition

Linux
OS X
Windows

Data scheme

schema-free

yes

predefined scheme

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.

Secondary indexes

yes

SQL

Support of SQL

yes

through the embedded Spark runtime

APIs and other access methods

RESTful HTTP API

gRPC
JSON over HTTP

ADO.NET
DB2 Connect
JDBC
ODBC
RESTful HTTP API

HTTP REST

Supported programming languages

.Net
ColdFusion
Erlang
Groovy
Java
JavaScript
Perl
PHP
Python
Ruby

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

C
C#
C++
Cobol
Delphi
Fortran
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
R
Ruby
Scala
Visual Basic

Server-side scripts

Stored procedures

yes

Triggers

yes

by integration with AWS Lambda

yes, watching key changes

Partitioning methods

Methods for storing different data on different nodes

Sharding

based on HBase

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Using Raft consensus algorithm to ensure data replication with strong consistency among multiple replicas.

Active-active shard replication

selectable replication factor

based on HBase

MapReduce

Offers an API for user-defined Map/Reduce methods

may be implemented via Amazon Elastic MapReduce (Amazon EMR)

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency
Immediate Consistency

can be specified for read operations

Immediate Consistency

Eventual Consistency

Immediate Consistency

Foreign keys

Referential integrity

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

Concurrency

Support for concurrent manipulation of data

yes

No - written data is immutable

yes

Durability

Support for making data persistent

yes

Yes - Synchronous writes to local disk combined with replication and asynchronous writes in parquet format to permanent shared storage

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)

fine grained access rights according to SQL-standard

Users with fine-grained authorization concept

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