DBMS > Amazon DynamoDB vs. CockroachDB vs. Databend vs. OpenMLDB

System Properties Comparison Amazon DynamoDB vs. CockroachDB vs. Databend vs. OpenMLDB

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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.

An open-source, elastic, and workload-aware cloud data warehouse designed to meet businesses' massive-scale analytics needs at low cost and with low complexity

An open-source machine learning database that provides a feature platform for training and inference

Primary database model

Document store
Key-value store

Relational DBMS

Time Series DBMS

Secondary database models

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	0.28
Rank	#287	Overall
	#131	Relational DBMS

Score	0.11
Rank	#339	Overall
	#30	Time Series DBMS

Website

aws.amazon.com/dynamodb

www.cockroachlabs.com

github.com/datafuselabs/databend
www.databend.com

openmldb.ai

Technical documentation

docs.aws.amazon.com/dynamodb

www.cockroachlabs.com/docs

docs.databend.com

openmldb.ai/docs/zh/main

Developer

Amazon

Cockroach Labs

Databend Labs

4 Paradigm Inc.

Initial release

2012

2015

2021

2020

Current release

24.1.0, May 2024

1.0.59, April 2023

2024-2 February 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 2.0

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

Rust

C++, Java, Scala

Server operating systems

hosted

Linux
macOS
Windows

hosted
Linux
macOS

Linux

Data scheme

schema-free

dynamic schema

yes

Fixed schema

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, wire compatible with PostgreSQL

yes

APIs and other access methods

RESTful HTTP API

JDBC

CLI Client
JDBC
RESTful HTTP API

JDBC
SQLAlchemy

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

Go
Java
JavaScript (Node.js)
Python
Rust

C++
Go
Java
Python
Scala

Server-side scripts

Stored procedures

Triggers

yes

by integration with AWS Lambda

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

none

horizontal partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Multi-source replication using RAFT

none

Source-replica replication

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

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

yes

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)

Role-based access control

Users with fine-grained authorization concept, user roles

fine grained access rights according to SQL-standard

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