DBMS > Amazon DocumentDB vs. Dragonfly vs. Sequoiadb

System Properties Comparison Amazon DocumentDB vs. Dragonfly vs. Sequoiadb

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Editorial information provided by DB-Engines

Name

Description

Fast, scalable, highly available, and fully managed MongoDB-compatible database service

A drop-in Redis replacement that scales vertically to support millions of operations per second and terabyte sized workloads, all on a single instance

NewSQL database with distributed OLTP and SQL

Primary database model

Document store

Key-value store

Document store
Relational DBMS

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

Score	1.84
Rank	#127	Overall
	#23	Document stores

Score	0.52
Rank	#245	Overall
	#35	Key-value stores

Score	0.39
Rank	#265	Overall
	#41	Document stores
	#123	Relational DBMS

Website

aws.amazon.com/documentdb

github.com/dragonflydb/dragonfly
www.dragonflydb.io

www.sequoiadb.com

Technical documentation

aws.amazon.com/documentdb/resources

www.dragonflydb.io/docs

www.sequoiadb.com/en/index.php?m=Files&a=index

Developer

DragonflyDB team and community contributors

Sequoiadb Ltd.

Initial release

2019

2023

2013

Current release

1.0, March 2023

License

Commercial or Open Source

commercial

Open Source

BSL 1.1

Open Source

Server: AGPL; Client: Apache V2

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++

Server operating systems

hosted

Linux

Data scheme

schema-free

scheme-free

schema-free

Typing

predefined data types such as float or date

yes

strings, hashes, lists, sets, sorted sets, bit arrays

yes

oid, date, timestamp, binary, regex

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

SQL-like query language

APIs and other access methods

proprietary protocol using JSON (MongoDB compatible)

Proprietary protocol

RESP - REdis Serialization Protocol

proprietary protocol using JSON

Supported programming languages

Go
Java
JavaScript (Node.js)
PHP
Python

C
C#
C++
Clojure
D
Dart
Elixir
Erlang
Go
Haskell
Java
JavaScript (Node.js)
Lisp
Lua
Objective-C
Perl
PHP
Python
R
Ruby
Rust
Scala
Swift
Tcl

.Net
C++
Java
PHP
Python

Server-side scripts

Stored procedures

Lua

JavaScript

Triggers

publish/subscribe channels provide some trigger functionality

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-availability zones for high availability, asynchronous replication for up to 15 read replicas

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

Immediate Consistency

Eventual Consistency

Foreign keys

Referential integrity

typically not used, however similar functionality with DBRef possible

Transaction concepts

Support to ensure data integrity after non-atomic manipulations of data

Atomic single-document operations

Atomic execution of command blocks and scripts

Document is locked during a transaction

Concurrency

Support for concurrent manipulation of data

yes

yes, strict serializability by the server

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

Password-based authentication

simple password-based access control

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More resources

Recent citations in the news

Unlock the power of parallel indexing in Amazon DocumentDB
19 June 2024, AWS Blog

Unlocking Semantic Search: Building Powerful Applications with Vector Search in Amazon DocumentDB
22 November 2024, AWS Blog

Amazon DocumentDB zero-ETL integration with Amazon OpenSearch Service is now available
16 May 2024, AWS Blog

Reduce cost and improve performance by migrating to Amazon DocumentDB 5.0
15 April 2024, AWS Blog

AWS announces Amazon DocumentDB zero-ETL integration with Amazon OpenSearch Service
16 May 2024, AWS Blog

provided by Google News

DragonflyDB Announces $21m in New Funding and General Availability
21 March 2023, Business Wire

DragonflyDB reels in $21M for its speedy in-memory database
21 March 2023, SiliconANGLE News

Tip the scale in your favour during interviews
20 July 2024, substack.com

Intel Linux Kernel Optimizations Show Huge Benefit For High Core Count Servers
29 March 2023, Phoronix

New Kubernetes Operator for Dragonfly In-Memory Datastore Now Available for Simplified Operations and Increased Performance
18 April 2023, Business Wire

provided by Google News

Continuously recognized by Gartner and Forrester, SequoiaDB consolidates its leading position in China's distributed database market
9 March 2023, PR Newswire

provided by Google News

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