DBMS > Amazon Aurora vs. Datomic vs. OrigoDB vs. ReductStore

System Properties Comparison Amazon Aurora vs. Datomic vs. OrigoDB vs. ReductStore

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Editorial information provided by DB-Engines

Name

Description

MySQL and PostgreSQL compatible cloud service by Amazon

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

A fully ACID in-memory object graph database

Designed to manage unstructured time-series data efficiently, providing unique features such as storing time-stamped blobs with labels, customizable data retention policies, and a straightforward FIFO quota system.

Primary database model

Relational DBMS

Document store
Object oriented DBMS

Time Series DBMS

Secondary database models

Document store

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

Score	7.91
Rank	#50	Overall
	#32	Relational DBMS

Score	1.59
Rank	#150	Overall
	#69	Relational DBMS

Score	0.00
Rank	#383	Overall
	#53	Document stores
	#20	Object oriented DBMS

Score	0.00
Rank	#383	Overall
	#41	Time Series DBMS

Website

aws.amazon.com/rds/aurora

www.datomic.com

origodb.com

github.com/reductstore
www.reduct.store

Technical documentation

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

docs.datomic.com

origodb.com/docs

www.reduct.store/docs

Developer

Amazon

Cognitect

Robert Friberg et al

ReductStore LLC

Initial release

2015

2012

2009

under the name LiveDB

2023

Current release

1.0.6735, June 2023

1.9, March 2024

License

Commercial or Open Source

commercial

limited edition free

Open Source

Business Source License 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

Java, Clojure

C++, Rust

Server operating systems

hosted

All OS with a Java VM

Linux
Windows

Docker
Linux
macOS
Windows

Data scheme

yes

Typing

predefined data types such as float or date

yes

User defined using .NET types and collections

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

can be achieved using .NET

Secondary indexes

yes

SQL

Support of SQL

yes

APIs and other access methods

ADO.NET
JDBC
ODBC

RESTful HTTP API

.NET Client API
HTTP API
LINQ

HTTP 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

Clojure
Java

.Net

C++
JavaScript (Node.js)
Python
Rust

Server-side scripts

Stored procedures

yes

Transaction Functions

yes

Triggers

yes

By using transaction functions

yes

Domain Events

Partitioning methods

Methods for storing different data on different nodes

horizontal partitioning

none

But extensive use of caching in the application peers

horizontal partitioning

client side managed; servers are not synchronized

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

none

But extensive use of caching in the application peers

Source-replica replication

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

depending on model

Transaction concepts

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

ACID

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

Write ahead log

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

Role based authorization

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More resources

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