DBMS > Amazon Redshift vs. Datomic vs. GeoSpock vs. IBM Db2 warehouse

System Properties Comparison Amazon Redshift vs. Datomic vs. GeoSpock vs. IBM Db2 warehouse

Please select another system to include it in the comparison.

Editorial information provided by DB-Engines

Name

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

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

Spatial and temporal data processing engine for extreme data scale

Cloud-based data warehousing service

Primary database model

Relational DBMS

Secondary database models

Time Series DBMS

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

Score	16.88
Rank	#35	Overall
	#22	Relational DBMS

Score	1.66
Rank	#144	Overall
	#66	Relational DBMS

Score	1.37
Rank	#160	Overall
	#74	Relational DBMS

Website

aws.amazon.com/redshift

www.datomic.com

geospock.com

www.ibm.com/products/db2/warehouse

Technical documentation

docs.aws.amazon.com/redshift

docs.datomic.com

Developer

Amazon (based on PostgreSQL)

Cognitect

GeoSpock

IBM

Initial release

2012

2014

Current release

1.0.7075, December 2023

2.0, September 2019

License

Commercial or Open Source

commercial

limited edition free

commercial

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

Java, Javascript

Server operating systems

hosted

All OS with a Java VM

hosted

Data scheme

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.

Import/export of XML data possible

Secondary indexes

restricted

yes

temporal, categorical

yes

SQL

Support of SQL

yes

does not fully support an SQL-standard

ANSI SQL for query only (using Presto)

yes

APIs and other access methods

JDBC
ODBC

RESTful HTTP API

JDBC

.NET Client API
JDBC
ODBC
OLE DB

Supported programming languages

All languages supporting JDBC/ODBC

Clojure
Java

Java
JavaScript (Node.js)
Perl
PHP
Python
R
Ruby

Server-side scripts

Stored procedures

user defined functions

in Python

yes

Transaction Functions

PL/SQL, SQL PL

Triggers

By using transaction functions

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

But extensive use of caching in the application peers

Automatic sharding

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

yes

none

But extensive use of caching in the application peers

yes

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

yes

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

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

Access rights for users can be defined per table

fine grained access rights according to SQL-standard

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.