DBMS > Amazon DynamoDB vs. Amazon Redshift vs. Apache Druid vs. Immudb

System Properties Comparison Amazon DynamoDB vs. Amazon Redshift vs. Apache Druid vs. Immudb

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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

Large scale data warehouse service for use with business intelligence tools

Open-source analytics data store designed for sub-second OLAP queries on high dimensionality and high cardinality data

An open source immutable (append-only) database with cryptographic verification which makes it tamper-resistant and fully auditable.

Primary database model

Document store
Key-value store

Relational DBMS

Relational DBMS
Time Series DBMS

Key-value store

Secondary database models

Relational DBMS

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

Score	74.45
Rank	#17	Overall
	#3	Document stores
	#2	Key-value stores

Score	16.88
Rank	#35	Overall
	#22	Relational DBMS

Score	3.25
Rank	#90	Overall
	#47	Relational DBMS
	#7	Time Series DBMS

Score	0.31
Rank	#295	Overall
	#42	Key-value stores

Website

aws.amazon.com/dynamodb

aws.amazon.com/redshift

druid.apache.org

github.com/codenotary/immudb
immudb.io

Technical documentation

docs.aws.amazon.com/dynamodb

docs.aws.amazon.com/redshift

druid.apache.org/docs/latest/design

docs.immudb.io

Developer

Amazon

Amazon (based on PostgreSQL)

Apache Software Foundation and contributors

Codenotary

Initial release

2012

2020

Current release

29.0.1, April 2024

1.2.3, April 2022

License

Commercial or Open Source

commercial

free tier for a limited amount of database operations

commercial

Open Source

Apache license v2

Open Source

Apache Version 2.0

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

Server operating systems

hosted

Linux
OS X
Unix

BSD
Linux
macOS
Solaris
Windows
z/OS

Data scheme

schema-free

yes

schema-less columns are supported

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.

Secondary indexes

yes

restricted

yes

SQL

Support of SQL

yes

does not fully support an SQL-standard

SQL for querying

SQL-like syntax

APIs and other access methods

RESTful HTTP API

JDBC
ODBC

JDBC
RESTful HTTP/JSON API

gRPC protocol
PostgreSQL wire protocol

Supported programming languages

.Net
ColdFusion
Erlang
Groovy
Java
JavaScript
Perl
PHP
Python
Ruby

All languages supporting JDBC/ODBC

Clojure
JavaScript
PHP
Python
R
Ruby
Scala

.Net
Go
Java
JavaScript (Node.js)
Python

Server-side scripts

Stored procedures

user defined functions

in Python

Triggers

yes

by integration with AWS Lambda

Partitioning methods

Methods for storing different data on different nodes

Sharding

manual/auto, time-based

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

yes

yes, via HDFS, S3 or other storage engines

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

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

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

ACID

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)

fine grained access rights according to SQL-standard

RBAC using LDAP or Druid internals for users and groups for read/write by datasource and system

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