DBMS > Amazon Aurora vs. Cachelot.io vs. PostgreSQL vs. Prometheus vs. RethinkDB

System Properties Comparison Amazon Aurora vs. Cachelot.io vs. PostgreSQL vs. Prometheus vs. RethinkDB

Editorial information provided by DB-Engines

Name

Description

MySQL and PostgreSQL compatible cloud service by Amazon

In-memory caching system

Widely used open source RDBMS

Developed as objectoriented DBMS (Postgres), gradually enhanced with 'standards' like SQL

Open-source Time Series DBMS and monitoring system

DBMS for the Web with a mechanism to push updated query results to applications in realtime.

Primary database model

Relational DBMS

Key-value store

Relational DBMS

with object oriented extensions, e.g.: user defined types/functions and inheritance. Handling of key/value pairs with hstore module.

Time Series DBMS

Document store

Secondary database models

Document store

Document store
Graph DBMS

with Apache Age
Spatial DBMS
Vector DBMS

with pgvector extension

Spatial DBMS

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

Score	7.91
Rank	#50	Overall
	#32	Relational DBMS

Score	0.00
Rank	#383	Overall
	#60	Key-value stores

Score	645.54
Rank	#4	Overall
	#4	Relational DBMS

Score	8.42
Rank	#47	Overall
	#2	Time Series DBMS

Score	2.74
Rank	#105	Overall
	#19	Document stores

Website

aws.amazon.com/rds/aurora

Technical documentation

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

www.postgresql.org/docs

prometheus.io/docs

rethinkdb.com/docs

Developer

Amazon

PostgreSQL Global Development Group

www.postgresql.org/developer

The Linux Foundation

since July 2017

Initial release

2015

1989

1989: Postgres, 1996: PostgreSQL

2015

2009

Current release

16.3, May 2024

2.4.1, August 2020

License

Commercial or Open Source

commercial

Open Source

Simplified BSD License

Open Source

BSD

Open Source

Apache 2.0

Open Source

Apache Version 2

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.

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Implementation language

C++

Server operating systems

hosted

FreeBSD
Linux
OS X

FreeBSD
HP-UX
Linux
NetBSD
OpenBSD
OS X
Solaris
Unix
Windows

Linux
Windows

Linux
OS X
Windows

Data scheme

yes

schema-free

yes

schema-free

Typing

predefined data types such as float or date

yes

Numeric data only

yes

string, binary, float, bool, date, geometry

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

specific XML-type available, but no XML query functionality.

Import of XML data possible

Secondary indexes

yes

SQL

Support of SQL

yes

standard with numerous extensions

APIs and other access methods

ADO.NET
JDBC
ODBC

Memcached protocol

ADO.NET
JDBC
native C library
ODBC
streaming API for large objects

RESTful HTTP/JSON API

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

.Net
C
C++
ColdFusion
Erlang
Java
Lisp
Lua
OCaml
OCaml
Perl
PHP
Python
Ruby

.Net
C
C++
Delphi
Java

JDBC
JavaScript (Node.js)
Perl
PHP
Python
Tcl

.Net
C++
Go
Haskell
Java
JavaScript (Node.js)
Python
Ruby

community-supported driver
C#

community-supported driver
C++

community-supported driver
Clojure

community-supported driver
Dart

community-supported driver
Erlang

community-supported driver
Go

community-supported driver
Haskell

community-supported driver
Java

official driver
JavaScript (Node.js)

official driver
Lisp

community-supported driver
Lua

community-supported driver
Objective-C

community-supported driver
Perl

community-supported driver
PHP

community-supported driver
Python

official driver
Ruby

official driver
Scala

community-supported driver

Server-side scripts

Stored procedures

yes

user defined functions

realized in proprietary language PL/pgSQL or with common languages like Perl, Python, Tcl etc.

Triggers

yes

Client-side triggers through changefeeds

Partitioning methods

Methods for storing different data on different nodes

horizontal partitioning

none

partitioning by range, list and (since PostgreSQL 11) by hash

Sharding

range based

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

none

Source-replica replication

other methods possible by using 3rd party extensions

yes

by Federation

Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

none

Immediate Consistency

none

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

Atomic single-document operations

Concurrency

Support for concurrent manipulation of data

yes

MVCC based

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

fine grained access rights according to SQL-standard

yes

users and table-level permissions

More information provided by the system vendor

We invite representatives of system vendors to contact us for updating and extending the system information,
and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.

Related products and services

3rd parties

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