DBMS > Amazon DynamoDB vs. RocksDB vs. YTsaurus

System Properties Comparison Amazon DynamoDB vs. RocksDB vs. YTsaurus

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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

Embeddable persistent key-value store optimized for fast storage (flash and RAM)

YTsaurus is an open source platform for distributed storage and processing.

Primary database model

Document store
Key-value store

Key-value store

Document store
Key-value store

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

Score	74.07
Rank	#17	Overall
	#3	Document stores
	#2	Key-value stores

Score	3.65
Rank	#85	Overall
	#11	Key-value stores

Score	0.11
Rank	#340	Overall
	#45	Document stores
	#50	Key-value stores

Website

aws.amazon.com/dynamodb

rocksdb.org

ytsaurus.tech

Technical documentation

docs.aws.amazon.com/dynamodb

github.com/facebook/rocksdb/wiki

ytsaurus.tech/docs/en

Developer

Amazon

Facebook, Inc.

Yandex

Initial release

2012

2013

2023

Current release

8.11.4, April 2024

License

Commercial or Open Source

commercial

free tier for a limited amount of database operations

Open Source

BSD

Open Source

Apache License, 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

C++

Server operating systems

hosted

Linux

Ubuntu

Data scheme

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

SQL

Support of SQL

YQL, an SQL-based language, is supported

APIs and other access methods

RESTful HTTP API

C++ API
Java API

Supported programming languages

.Net
ColdFusion
Erlang
Groovy
Java
JavaScript
Perl
PHP
Python
Ruby

C
C++
Go
Java
Perl
Python
Ruby

C++
Go
Java
JavaScript
Python

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

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

yes

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

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

yes

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)

Access Control Lists

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