DBMS > Amazon DynamoDB vs. ReductStore vs. RocksDB vs. TerarkDB

System Properties Comparison Amazon DynamoDB vs. ReductStore vs. RocksDB vs. TerarkDB

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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

Designed to manage unstructured time-series data efficiently, providing unique features such as storing time-stamped blobs with labels, customizable data retention policies, and a straightforward FIFO quota system.

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

A key-value store forked from RocksDB with advanced compression algorithms. It can be used standalone or as a storage engine for MySQL and MongoDB

Primary database model

Document store
Key-value store

Time Series DBMS

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	0.00
Rank	#383	Overall
	#41	Time Series DBMS

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

Score	0.00
Rank	#383	Overall
	#60	Key-value stores

Website

aws.amazon.com/dynamodb

github.com/reductstore
www.reduct.store

rocksdb.org

github.com/bytedance/terarkdb

Technical documentation

docs.aws.amazon.com/dynamodb

www.reduct.store/docs

github.com/facebook/rocksdb/wiki

bytedance.larkoffice.com/docs/doccnZmYFqHBm06BbvYgjsHHcKc

Developer

Amazon

ReductStore LLC

Facebook, Inc.

ByteDance, originally Terark

Initial release

2012

2023

2013

2016

Current release

1.9, March 2024

8.11.4, April 2024

License

Commercial or Open Source

commercial

free tier for a limited amount of database operations

Open Source

Business Source License 1.1

Open Source

BSD

commercial

restricted open source version available

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

C++, Rust

C++

Server operating systems

hosted

Docker
Linux
macOS
Windows

Linux

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

APIs and other access methods

RESTful HTTP API

HTTP API

C++ API
Java API

Supported programming languages

.Net
ColdFusion
Erlang
Groovy
Java
JavaScript
Perl
PHP
Python
Ruby

C++
JavaScript (Node.js)
Python
Rust

C
C++
Go
Java
Perl
Python
Ruby

C++
Java

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

none

Replication methods

Methods for redundantly storing data on multiple nodes

yes

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

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

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)

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