DBMS > Amazon Aurora vs. Amazon CloudSearch vs. Amazon Redshift vs. Datomic vs. HarperDB

System Properties Comparison Amazon Aurora vs. Amazon CloudSearch vs. Amazon Redshift vs. Datomic vs. HarperDB

Editorial information provided by DB-Engines

Name

Description

MySQL and PostgreSQL compatible cloud service by Amazon

A hosted search engine service by Amazon with the data stored in Amazons cloud

Large scale data warehouse service for use with business intelligence tools

Datomic builds on immutable values, supports point-in-time queries and uses 3rd party systems for durability

Ultra-low latency distributed database with an intuitive REST API supporting NoSQL and SQL (including joins). Deployment of functions and databases simultaneously with a consolidated node-level architecture.

Primary database model

Secondary database models

Document store

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

Score	7.57
Rank	#51	Overall
	#32	Relational DBMS

Score	1.81
Rank	#137	Overall
	#12	Search engines

Score	16.88
Rank	#35	Overall
	#22	Relational DBMS

Score	1.66
Rank	#144	Overall
	#66	Relational DBMS

Score	0.60
Rank	#244	Overall
	#38	Document stores

Website

aws.amazon.com/rds/aurora

aws.amazon.com/cloudsearch

aws.amazon.com/redshift

www.datomic.com

www.harperdb.io

Technical documentation

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

docs.aws.amazon.com/cloudsearch

docs.aws.amazon.com/redshift

docs.datomic.com

docs.harperdb.io/docs

Developer

Amazon

Amazon (based on PostgreSQL)

Cognitect

HarperDB

Initial release

2015

2012

2017

Current release

1.0.7075, December 2023

3.1, August 2021

License

Commercial or Open Source

commercial

limited edition free

commercial

free community edition available

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, Clojure

Node.js

Server operating systems

hosted

All OS with a Java VM

Linux
OS X

Data scheme

yes

dynamic schema

Typing

predefined data types such as float or date

yes

JSON data types

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

all search fields are automatically indexed

restricted

yes

SQL

Support of SQL

yes

does not fully support an SQL-standard

SQL-like data manipulation statements

APIs and other access methods

ADO.NET
JDBC
ODBC

HTTP API

JDBC
ODBC

RESTful HTTP API

JDBC
ODBC
React Hooks
RESTful HTTP/JSON API
WebSocket

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

All languages supporting JDBC/ODBC

Clojure
Java

.Net
C
C#
C++
ColdFusion
D
Dart
Delphi
Erlang
Go
Haskell
Java
JavaScript (Node.js)
Lisp
MatLab
Objective C
Perl
PHP
PowerShell
Prolog
Python
R
Ruby
Rust
Scala
Swift

Server-side scripts

Stored procedures

yes

user defined functions

in Python

yes

Transaction Functions

Custom Functions

since release 3.1

Triggers

yes

By using transaction functions

Partitioning methods

Methods for storing different data on different nodes

horizontal partitioning

yes

automatic partitioning across Amazon Search Instance as required

Sharding

none

But extensive use of caching in the application peers

A table resides as a whole on one (or more) nodes in a cluster

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

yes

managed transparently by AWS

yes

none

But extensive use of caching in the application peers

yes

the nodes on which a table resides can be defined

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Foreign keys

Referential integrity

yes

informational only, not enforced by the system

Transaction concepts

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

ACID

Atomic execution of specific operations

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

using external storage systems (e.g. Cassandra, DynamoDB, PostgreSQL, Couchbase and others)

yes, using LMDB

In-memory capabilities

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

yes

recommended only for testing and development

yes

User concepts

Access control

fine grained access rights according to SQL-standard

authentication via encrypted signatures

fine grained access rights according to SQL-standard

Access rights for users and roles

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