DBMS > Cachelot.io vs. Cloudflare Workers KV vs. IBM Db2 warehouse vs. Microsoft Azure Cosmos DB vs. Microsoft Azure Table Storage

System Properties Comparison Cachelot.io vs. Cloudflare Workers KV vs. IBM Db2 warehouse vs. Microsoft Azure Cosmos DB vs. Microsoft Azure Table Storage

Editorial information provided by DB-Engines

Name

Description

In-memory caching system

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

Cloud-based data warehousing service

Globally distributed, horizontally scalable, multi-model database service

A Wide Column Store for rapid development using massive semi-structured datasets

Primary database model

Key-value store

Relational DBMS

Document store
Graph DBMS
Key-value store
Wide column store

Wide column store

Secondary database models

Spatial DBMS

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

Score	0.04
Rank	#388	Overall
	#62	Key-value stores

Score	0.39
Rank	#274	Overall
	#39	Key-value stores

Score	1.37
Rank	#160	Overall
	#74	Relational DBMS

Score	27.71
Rank	#27	Overall
	#4	Document stores
	#2	Graph DBMS
	#3	Key-value stores
	#3	Wide column stores

Score	4.04
Rank	#77	Overall
	#6	Wide column stores

Website

cachelot.io

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

www.ibm.com/products/db2/warehouse

azure.microsoft.com/services/cosmos-db

azure.microsoft.com/en-us/services/storage/tables

Technical documentation

developers.cloudflare.com/kv/api

learn.microsoft.com/azure/cosmos-db

Developer

Cloudflare

IBM

Microsoft

Initial release

2015

2018

2014

2012

License

Commercial or Open Source

Open Source

Simplified BSD License

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

C++

Server operating systems

FreeBSD
Linux
OS X

hosted

Data scheme

schema-free

yes

schema-free

Typing

predefined data types such as float or date

yes

JSON types

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

yes

All properties auto-indexed by default

SQL

Support of SQL

yes

SQL-like query language

APIs and other access methods

Memcached protocol

HTTP REST
Proprietary protocol

.NET Client API
JDBC
ODBC
OLE DB

DocumentDB API
Graph API (Gremlin)
MongoDB API
RESTful HTTP API
Table API

RESTful HTTP API

Supported programming languages

.Net
C
C++
ColdFusion
Erlang
Java
Lisp
Lua
OCaml
OCaml
Perl
PHP
Python
Ruby

C
C++
Dart
JavaScript
Kotlin
Python
Rust
Scala

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

.Net
C#
Java
JavaScript
JavaScript (Node.js)
MongoDB client drivers written for various programming languages
Python

.Net
C#
C++
Java
JavaScript (Node.js)
PHP
Python
Ruby

Server-side scripts

Stored procedures

PL/SQL, SQL PL

JavaScript

Triggers

yes

JavaScript

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

Implicit feature of the cloud service

Sharding

Implicit feature of the cloud service

Replication methods

Methods for redundantly storing data on multiple nodes

none

yes

Implicit feature of the cloud service

yes

implicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.

MapReduce

Offers an API for user-defined Map/Reduce methods

with Hadoop integration

Integration with Hadoop/HDInsight on Azure*

Consistency concepts

Methods to ensure consistency in a distributed system

none

Eventual Consistency

Immediate Consistency

Bounded Staleness
Consistent Prefix
Eventual Consistency
Immediate Consistency

Consistency level configurable on request level
Session Consistency

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

Multi-item ACID transactions with snapshot isolation within a partition

optimistic locking

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

In-memory capabilities

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

yes

User concepts

Access control

fine grained access rights according to SQL-standard

Access rights can be defined down to the item level

Access rights based on private key authentication or shared access signatures

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