DBMS > Amazon DocumentDB vs. Apache Derby vs. Dragonfly

System Properties Comparison Amazon DocumentDB vs. Apache Derby vs. Dragonfly

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Editorial information provided by DB-Engines

Name

Description

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

Full-featured RDBMS with a small footprint, either embedded into a Java application or used as a database server.

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

Primary database model

Document store

Relational DBMS

Key-value store

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

Score	1.84
Rank	#127	Overall
	#23	Document stores

Score	3.80
Rank	#73	Overall
	#39	Relational DBMS

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

Website

aws.amazon.com/documentdb

db.apache.org/derby

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

Technical documentation

aws.amazon.com/documentdb/resources

db.apache.org/derby/manuals/index.html

www.dragonflydb.io/docs

Developer

Apache Software Foundation

DragonflyDB team and community contributors

Initial release

2019

1997

2023

Current release

10.17.1.0, November 2023

1.0, March 2023

License

Commercial or Open Source

commercial

Open Source

Apache version 2

Open Source

BSL 1.1

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

Java

C++

Server operating systems

hosted

All OS with a Java VM

Linux

Data scheme

schema-free

yes

scheme-free

Typing

predefined data types such as float or date

yes

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

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.

yes

Secondary indexes

yes

SQL

Support of SQL

yes

APIs and other access methods

proprietary protocol using JSON (MongoDB compatible)

JDBC

Proprietary protocol

RESP - REdis Serialization Protocol

Supported programming languages

Go
Java
JavaScript (Node.js)
PHP
Python

Java

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

Server-side scripts

Stored procedures

Java Stored Procedures

Lua

Triggers

yes

publish/subscribe channels provide some trigger functionality

Partitioning methods

Methods for storing different data on different nodes

none

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

yes

Transaction concepts

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

Atomic single-document operations

ACID

Atomic execution of command blocks and scripts

Concurrency

Support for concurrent manipulation of data

yes

yes, strict serializability by the server

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

fine grained access rights according to SQL-standard

Password-based authentication

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