DBMS > Amazon DocumentDB vs. Dragonfly vs. MySQL vs. Rockset vs. SpatiaLite

System Properties Comparison Amazon DocumentDB vs. Dragonfly vs. MySQL vs. Rockset vs. SpatiaLite

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

Widely used open source RDBMS

A scalable, reliable search and analytics service in the cloud, built on RocksDB

Spatial extension of SQLite

Primary database model

Document store

Key-value store

Relational DBMS

Key/Value like access via memcached API

Document store

Spatial DBMS

Secondary database models

Document store
Spatial DBMS

Relational DBMS
Search engine

Relational DBMS

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

Score	1.91
Rank	#132	Overall
	#24	Document stores

Score	0.41
Rank	#266	Overall
	#38	Key-value stores

Score	1083.74
Rank	#2	Overall
	#2	Relational DBMS

Score	0.79
Rank	#211	Overall
	#35	Document stores

Score	1.60
Rank	#149	Overall
	#3	Spatial DBMS

Website

aws.amazon.com/documentdb

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

www.mysql.com

rockset.com

www.gaia-gis.it/fossil/libspatialite/index

Technical documentation

aws.amazon.com/documentdb/resources

www.dragonflydb.io/docs

dev.mysql.com/doc

docs.rockset.com

www.gaia-gis.it/gaia-sins/spatialite_topics.html

Developer

DragonflyDB team and community contributors

Oracle

since 2010, originally MySQL AB, then Sun

Rockset

Alessandro Furieri

Initial release

2019

2023

1995

2019

2008

Current release

1.0, March 2023

8.4.0, April 2024

5.0.0, August 2020

License

Commercial or Open Source

commercial

Open Source

BSL 1.1

Open Source

GPL version 2. Commercial licenses with extended functionallity are available

commercial

Open Source

MPL 1.1, GPL v2.0 or LGPL v2.1

Cloud-based only

Only available as a cloud service

yes

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Implementation language

C++

C and C++

C++

Server operating systems

hosted

Linux

FreeBSD
Linux
OS X
Solaris
Windows

hosted

server-less

Data scheme

schema-free

scheme-free

yes

schema-free

yes

Typing

predefined data types such as float or date

yes

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

yes

dynamic typing

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.

yes

ingestion from XML files supported

Secondary indexes

yes

all fields are automatically indexed

yes

SQL

Support of SQL

yes

with proprietary extensions

Read-only SQL queries, including JOINs

yes

APIs and other access methods

proprietary protocol using JSON (MongoDB compatible)

Proprietary protocol

RESP - REdis Serialization Protocol

ADO.NET
JDBC
ODBC
Proprietary native API

HTTP REST

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

Ada
C
C#
C++
D
Delphi
Eiffel
Erlang
Haskell
Java
JavaScript (Node.js)
Objective-C
OCaml
Perl
PHP
Python
Ruby
Scheme
Tcl

Go
Java
JavaScript (Node.js)
Python

Server-side scripts

Stored procedures

Lua

yes

proprietary syntax

Triggers

publish/subscribe channels provide some trigger functionality

yes

Partitioning methods

Methods for storing different data on different nodes

none

horizontal partitioning, sharding with MySQL Cluster or MySQL Fabric

Automatic sharding

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

Multi-source replication
Source-replica replication

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

Immediate Consistency

Eventual Consistency

Immediate Consistency

Eventual Consistency

Foreign keys

Referential integrity

typically not used, however similar functionality with DBRef possible

yes

not for MyISAM storage engine

yes

Transaction concepts

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

Atomic single-document operations

Atomic execution of command blocks and scripts

ACID

not for MyISAM storage engine

ACID

Concurrency

Support for concurrent manipulation of data

yes

yes, strict serializability by the server

yes

table locks or row locks depending on storage engine

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

Users with fine-grained authorization concept

no user groups or roles

Access rights for users and organizations can be defined via Rockset console

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