DBMS > Amazon Redshift vs. Datomic vs. Oracle Coherence vs. SpatiaLite

System Properties Comparison Amazon Redshift vs. Datomic vs. Oracle Coherence vs. SpatiaLite

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Editorial information provided by DB-Engines

Name

Description

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

Oracles in-memory data grid solution

Spatial extension of SQLite

Primary database model

Relational DBMS

Key-value store

Spatial DBMS

Secondary database models

Relational DBMS

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

Score	19.03
Rank	#34	Overall
	#21	Relational DBMS

Score	1.76
Rank	#145	Overall
	#66	Relational DBMS

Score	2.02
Rank	#131	Overall
	#22	Key-value stores

Score	1.72
Rank	#149	Overall
	#3	Spatial DBMS

Website

aws.amazon.com/redshift

www.datomic.com

www.oracle.com/java/coherence

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

Technical documentation

docs.aws.amazon.com/redshift

docs.datomic.com

docs.oracle.com/en/middleware/standalone/coherence

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

Developer

Amazon (based on PostgreSQL)

Cognitect

Oracle

Alessandro Furieri

Initial release

2012

2007

2008

Current release

1.0.6735, June 2023

14.1, August 2023

5.0.0, August 2020

License

Commercial or Open Source

commercial

limited edition free

commercial

Open Source

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

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

Java

C++

Server operating systems

hosted

All OS with a Java VM

server-less

Data scheme

yes

schema-free

yes

Typing

predefined data types such as float or date

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.

Secondary indexes

restricted

yes

SQL

Support of SQL

yes

does not fully support an SQL-standard

yes

APIs and other access methods

JDBC
ODBC

RESTful HTTP API

JCache
JPA
RESTful HTTP API

Supported programming languages

All languages supporting JDBC/ODBC

Clojure
Java

.Net
C++
Java

Server-side scripts

Stored procedures

user defined functions

in Python

yes

Transaction Functions

Triggers

By using transaction functions

yes

Live Events

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

But extensive use of caching in the application peers

Sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

yes

none

But extensive use of caching in the application peers

yes, with selectable consistency level

none

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

informational only, not enforced by the system

yes

Transaction concepts

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

ACID

configurable

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

optionally

yes

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

authentification to access the cache via certificates or http basic authentication

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