DBMS > Amazon Aurora vs. Dragonfly vs. GeoSpock vs. MySQL vs. TerminusDB

System Properties Comparison Amazon Aurora vs. Dragonfly vs. GeoSpock vs. MySQL vs. TerminusDB

Editorial information provided by DB-Engines

Name

GeoSpock seems to be discontinued. Therefore it will be excluded from the DB-Engines ranking.

Description

MySQL and PostgreSQL compatible cloud service by Amazon

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

Spatial and temporal data processing engine for extreme data scale

Widely used open source RDBMS

Scalable Graph Database platform making enterprise data available by exploiting inferred entities and relationships

Primary database model

Relational DBMS

Key-value store

Relational DBMS

Key/Value like access via memcached API

Graph DBMS

Secondary database models

Document store

Time Series DBMS

Document store
Spatial DBMS

Document store
RDF store

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

Score	7.91
Rank	#50	Overall
	#32	Relational DBMS

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

Score	1083.74
Rank	#2	Overall
	#2	Relational DBMS

Score	0.17
Rank	#325	Overall
	#29	Graph DBMS

Website

aws.amazon.com/rds/aurora

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

geospock.com

www.mysql.com

terminusdb.com

Technical documentation

docs.aws.amazon.com/AmazonRDS/latest/AuroraUserGuide/CHAP_Aurora.html

www.dragonflydb.io/docs

dev.mysql.com/doc

terminusdb.github.io/terminusdb/#

Developer

Amazon

DragonflyDB team and community contributors

GeoSpock

Oracle

since 2010, originally MySQL AB, then Sun

DataChemist Ltd.

Initial release

2015

2023

1995

2018

Current release

1.0, March 2023

2.0, September 2019

8.4.0, April 2024

11.0.0, January 2023

License

Commercial or Open Source

commercial

Open Source

BSL 1.1

commercial

Open Source

GPL version 2. Commercial licenses with extended functionallity are available

Open Source

GPL V3

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

C++

Java, Javascript

C and C++

Prolog, Rust

Server operating systems

hosted

Linux

hosted

FreeBSD
Linux
OS X
Solaris
Windows

Linux

Data scheme

yes

scheme-free

yes

Typing

predefined data types such as float or date

yes

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

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

Secondary indexes

yes

temporal, categorical

yes

SQL

Support of SQL

yes

ANSI SQL for query only (using Presto)

yes

with proprietary extensions

SQL-like query language (WOQL)

APIs and other access methods

ADO.NET
JDBC
ODBC

Proprietary protocol

RESP - REdis Serialization Protocol

JDBC

ADO.NET
JDBC
ODBC
Proprietary native API

OWL
RESTful HTTP API
WOQL (Web Object Query Language)

Supported programming languages

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

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

JavaScript
Python

Server-side scripts

Stored procedures

yes

Lua

yes

proprietary syntax

yes

Triggers

yes

publish/subscribe channels provide some trigger functionality

yes

Partitioning methods

Methods for storing different data on different nodes

horizontal partitioning

Automatic sharding

horizontal partitioning, sharding with MySQL Cluster or MySQL Fabric

Graph Partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

Multi-source replication
Source-replica replication

Journaling Streams

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency

Immediate Consistency

Foreign keys

Referential integrity

yes

not for MyISAM storage engine

yes

Transaction concepts

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

ACID

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 journaling

In-memory capabilities

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

yes

User concepts

Access control

fine grained access rights according to SQL-standard

Password-based authentication

Access rights for users can be defined per table

Users with fine-grained authorization concept

no user groups or roles

Role-based access control

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