DBMS > Amazon DynamoDB vs. Citus vs. CrateDB vs. DuckDB

System Properties Comparison Amazon DynamoDB vs. Citus vs. CrateDB vs. DuckDB

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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

Scalable hybrid operational and analytics RDBMS for big data use cases based on PostgreSQL

Distributed Date Store based on Lucene

An embeddable, in-process, column-oriented SQL OLAP RDBMS

Primary database model

Document store
Key-value store

Relational DBMS

Relational DBMS
Search engine

Relational DBMS

Secondary database models

Document store

Document store
Time Series DBMS

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

Score	84.46
Rank	#16	Overall
	#2	Document stores
	#2	Key-value stores

Score	1.77
Rank	#135	Overall
	#65	Relational DBMS

Score	0.97
Rank	#178	Overall
	#86	Relational DBMS
	#13	Search engines

Score	0.34
Rank	#267	Overall
	#123	Relational DBMS

Website

aws.amazon.com/dynamodb

www.citusdata.com

crate.io

duckdb.org

Technical documentation

docs.aws.amazon.com/dynamodb

docs.citusdata.com

crate.io/docs

duckdb.org/docs

Developer

Amazon

Crate

Initial release

2012

2010

2013

2018

Current release

8.1, December 2018

0.2, August 2020

License

Commercial or Open Source

commercial

free tier for a limited amount of database operations

Open Source

AGPL, commercial license also available

Open Source

MIT License

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

C++

Server operating systems

hosted

Linux

All OS with a Java 7 (and higher) VM

server-less

Data scheme

schema-free

yes

Flexible Schema (defined schema, partial schema, schema free)

yes

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

specific XML type available, but no XML query functionality

Secondary indexes

yes

SQL

Support of SQL

yes

standard, with numerous extensions

yes, but no triggers and constraints

yes

APIs and other access methods

RESTful HTTP API

ADO.NET
JDBC
native C library
ODBC
streaming API for large objects

ADO.NET

community maintained client
JDBC
MQTT (Message Queue Telemetry Transport)
PostgreSQL wire protocol
Prometheus Remote Read/Write
RESTful HTTP API

CLI Client
JDBC

Supported programming languages

.Net
ColdFusion
Erlang
Groovy
Java
JavaScript
Perl
PHP
Python
Ruby

.Net
C
C++
Delphi
Java
JavaScript (Node.js)
Perl
PHP
Python
Tcl

Erlang
Go

community maintained client
Java
JavaScript (Node.js)

community maintained client
Perl

community maintained client
PHP
Python
Ruby

community maintained client
Scala

community maintained client

C
C++
Go

3rd party driver
Java
Python
R
Ruby

3rd party driver

Server-side scripts

Stored procedures

user defined functions

realized in proprietary language PL/pgSQL or with common languages like Perl, Python, Tcl etc.

user defined functions

Triggers

yes

by integration with AWS Lambda

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Source-replica replication

other methods possible by using 3rd party extensions

selectable replication factor

none

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
Read Your Own Writes Consistency

for primary key lookups

Immediate Consistency

Foreign keys

Referential integrity

yes

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

unique row identifiers can be used for implementing an optimistic concurrency control strategy

ACID

Concurrency

Support for concurrent manipulation of data

yes

yes, multi-version concurrency control (MVCC)

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

rights management via user accounts

More information provided by the system vendor

Specific characteristics

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Competitive advantages

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Typical application scenarios

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Key customers

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Market metrics

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Licensing and pricing models

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