DBMS > Amazon Redshift vs. Cloudflare Workers KV vs. Datomic vs. IBM Db2 vs. Kinetica

System Properties Comparison Amazon Redshift vs. Cloudflare Workers KV vs. Datomic vs. IBM Db2 vs. Kinetica

Editorial information provided by DB-Engines

Name

Description

Large scale data warehouse service for use with business intelligence tools

A global, low-latency, key-value store for applications on Cloudflare with exceptionally high read volumes and low-latency.

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

Common in IBM host environments, 2 different versions for host and Windows/Linux

Fully vectorized database across both GPUs and CPUs

Primary database model

Relational DBMS

Key-value store

Relational DBMS

Since Version 10.5 support for JSON/BSON documents compatible with MongoDB

Relational DBMS

Secondary database models

Document store
RDF store

in Db2 LUW (Linux, Unix, Windows)
Spatial DBMS

with Db2 Spatial Extender

Spatial DBMS
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	0.39
Rank	#274	Overall
	#39	Key-value stores

Score	1.66
Rank	#144	Overall
	#66	Relational DBMS

Score	125.90
Rank	#9	Overall
	#6	Relational DBMS

Score	0.66
Rank	#234	Overall
	#107	Relational DBMS

Website

aws.amazon.com/redshift

www.cloudflare.com/developer-platform/workers-kv

www.datomic.com

www.ibm.com/products/db2

www.kinetica.com

Technical documentation

docs.aws.amazon.com/redshift

developers.cloudflare.com/kv/api

docs.datomic.com

www.ibm.com/docs/en/db2

docs.kinetica.com

Developer

Amazon (based on PostgreSQL)

Cloudflare

Cognitect

IBM

Kinetica

Initial release

2012

2018

2012

1983

host version

2012

Current release

1.0.7075, December 2023

12.1, October 2016

7.1, August 2021

License

Commercial or Open Source

commercial

limited edition free

commercial

free version is available

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

C and C++

C, C++

Server operating systems

hosted

All OS with a Java VM

AIX
HP-UX
Linux
Solaris
Windows
z/OS

Linux

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

SQL-like DML and DDL statements

APIs and other access methods

JDBC
ODBC

HTTP REST
Proprietary protocol

RESTful HTTP API

ADO.NET
JDBC
JSON style queries

MongoDB compatible
ODBC
XQuery

JDBC
ODBC
RESTful HTTP API

Supported programming languages

All languages supporting JDBC/ODBC

C
C++
Dart
JavaScript
Kotlin
Python
Rust
Scala

Clojure
Java

C
C#
C++
Cobol
Delphi
Fortran
Java
Perl
PHP
Python
Ruby
Visual Basic

C++
Java
JavaScript (Node.js)
Python

Server-side scripts

Stored procedures

user defined functions

in Python

yes

Transaction Functions

yes

user defined functions

Triggers

By using transaction functions

yes

triggers when inserted values for one or more columns fall within a specified range

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

But extensive use of caching in the application peers

Sharding

only with Windows/Unix/Linux Version

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

yes

none

But extensive use of caching in the application peers

yes

with separate tools (MQ, InfoSphere)

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

Eventual Consistency

Immediate Consistency

Immediate Consistency or Eventual Consistency depending on configuration

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

GPU vRAM or System RAM

User concepts

Access control

fine grained access rights according to SQL-standard

Access rights for users and roles on table level

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