DBMS > Amazon DynamoDB vs. CockroachDB vs. CouchDB vs. CrateDB

System Properties Comparison Amazon DynamoDB vs. CockroachDB vs. CouchDB vs. CrateDB

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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

CockroachDB is a distributed database architected for modern cloud applications. It is wire compatible with PostgreSQL and backed by a Key-Value Store, which is either RocksDB or a purpose-built derivative, called Pebble.

A native JSON - document store inspired by Lotus Notes, scalable from globally distributed server-clusters down to mobile phones.

Distributed Database based on Lucene

Primary database model

Document store
Key-value store

Relational DBMS

Document store

Document store
Spatial DBMS
Search engine
Time Series DBMS
Vector DBMS

Secondary database models

Spatial DBMS

using the Geocouch extension

Relational 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	4.74
Rank	#67	Overall
	#36	Relational DBMS

Score	7.46
Rank	#51	Overall
	#7	Document stores

Score	0.69
Rank	#226	Overall
	#37	Document stores
	#5	Spatial DBMS
	#16	Search engines
	#19	Time Series DBMS
	#11	Vector DBMS

Website

aws.amazon.com/dynamodb

www.cockroachlabs.com

couchdb.apache.org

cratedb.com

Technical documentation

docs.aws.amazon.com/dynamodb

www.cockroachlabs.com/docs

docs.couchdb.org/en/stable

cratedb.com/docs

Developer

Amazon

Cockroach Labs

Apache Software Foundation

Apache top-level project, originally developed by Damien Katz, a former Lotus Notes developer

Crate

Initial release

2012

2015

2005

2013

Current release

24.1.0, May 2024

3.3.3, December 2023

5.8.1, August 2024

License

Commercial or Open Source

commercial

free tier for a limited amount of database operations

Open Source

Apache 2.0, commercial license available

Open Source

Apache version 2

Open Source

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

Erlang

Java

Server operating systems

hosted

Linux
macOS
Windows

Android
BSD
Linux
OS X
Solaris
Windows

All Operating Systems, including Kubernetes with CrateDB Kubernetes Operator support

Data scheme

schema-free

dynamic schema

schema-free

Flexible Schema (defined schema, partial schema, 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

via views

yes

SQL

Support of SQL

yes, wire compatible with PostgreSQL

yes, but no triggers and constraints, and PostgreSQL compatibility

APIs and other access methods

RESTful HTTP API

JDBC

RESTful HTTP/JSON API

ADO.NET
JDBC
ODBC
PostgreSQL wire protocol
Prometheus Remote Read/Write
RESTful HTTP API

Supported programming languages

.Net
ColdFusion
Erlang
Groovy
Java
JavaScript
Perl
PHP
Python
Ruby

C#
C++
Clojure
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
Rust

C
C#
ColdFusion
Erlang
Haskell
Java
JavaScript
Lisp
Lua
Objective-C
OCaml
Perl
PHP
PL/SQL
Python
Ruby
Smalltalk

.NET
Erlang
Go

community maintained client
Java
JavaScript (Node.js)

community maintained client
Perl

community maintained client
PHP
Python
R
Ruby

community maintained client
Scala

community maintained client

Server-side scripts

Stored procedures

View functions in JavaScript

user defined functions (Javascript)

Triggers

yes

by integration with AWS Lambda

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

horizontal partitioning (by key range)

all tables are translated to an ordered KV store and then broken down into 64MB ranges, which are then used as replicas in RAFT

Sharding

improved architecture with release 2.0

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Multi-source replication using RAFT

Multi-source replication
Source-replica replication

Configurable replication on table/partition-level

MapReduce

Offers an API for user-defined Map/Reduce methods

may be implemented via Amazon Elastic MapReduce (Amazon EMR)

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency
Immediate Consistency

can be specified for read operations

Immediate Consistency

Eventual Consistency

Eventual Consistency
Read-after-write consistency on record level

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

atomic operations within a single document possible

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

Concurrency

Support for concurrent manipulation of data

yes

strategy: optimistic locking

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.

User concepts

Access control

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

Role-based access control

Access rights for users can be defined per database

rights management via user accounts

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