DBMS > Amazon DocumentDB vs. Apache Drill vs. Dragonfly

System Properties Comparison Amazon DocumentDB vs. Apache Drill 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

Schema-free SQL Query Engine for Hadoop, NoSQL and Cloud Storage

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

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	1.82
Rank	#128	Overall
	#24	Document stores
	#60	Relational DBMS

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

Website

aws.amazon.com/documentdb

drill.apache.org

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

Technical documentation

aws.amazon.com/documentdb/resources

drill.apache.org/docs

www.dragonflydb.io/docs

Developer

Apache Software Foundation

DragonflyDB team and community contributors

Initial release

2019

2012

2023

Current release

1.20.3, January 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

Providers of DBaaS offerings, please contact us to be listed.

Implementation language

C++

Server operating systems

hosted

Linux
OS X
Windows

Linux

Data scheme

schema-free

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.

Secondary indexes

yes

SQL

Support of SQL

SQL SELECT statement is SQL:2003 compliant

APIs and other access methods

proprietary protocol using JSON (MongoDB compatible)

JDBC
ODBC
RESTful HTTP API

Proprietary protocol

RESP - REdis Serialization Protocol

Supported programming languages

Go
Java
JavaScript (Node.js)
PHP
Python

C++

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

user defined functions

Lua

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)

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

none

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

Concurrency

Support for concurrent manipulation of data

yes

yes, strict serializability by the server

Durability

Support for making data persistent

yes

Depending on the underlying data source

yes

In-memory capabilities

Is there an option to define some or all structures to be held in-memory only.

Depending on the underlying data source

yes

User concepts

Access control

Access rights for users and roles

Depending on the underlying data source

Password-based authentication

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More resources

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