DBMS > Databend vs. Memcached vs. Microsoft Azure Cosmos DB

System Properties Comparison Databend vs. Memcached vs. Microsoft Azure Cosmos DB

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Editorial information provided by DB-Engines

Name

Description

An open-source, elastic, and workload-aware cloud data warehouse designed to meet businesses' massive-scale analytics needs at low cost and with low complexity

In-memory key-value store, originally intended for caching

Globally distributed, horizontally scalable, multi-model database service

Primary database model

Relational DBMS

Key-value store

Document store
Graph DBMS
Key-value store
Wide column store

Secondary database models

Spatial DBMS

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

Score	0.34
Rank	#283	Overall
	#130	Relational DBMS

Score	18.08
Rank	#32	Overall
	#4	Key-value stores

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

Website

github.com/datafuselabs/databend
www.databend.com

www.memcached.org

azure.microsoft.com/services/cosmos-db

Technical documentation

docs.databend.com

github.com/memcached/memcached/wiki

learn.microsoft.com/azure/cosmos-db

Developer

Databend Labs

Danga Interactive

originally developed by Brad Fitzpatrick for LiveJournal

Microsoft

Initial release

2021

2003

2014

Current release

1.0.59, April 2023

1.6.27, May 2024

License

Commercial or Open Source

Open Source

Apache Version 2.0

Open Source

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

Rust

Server operating systems

hosted
Linux
macOS

FreeBSD
Linux
OS X
Unix
Windows

hosted

Data scheme

yes

schema-free

Typing

predefined data types such as float or date

yes

JSON types

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

yes

All properties auto-indexed by default

SQL

Support of SQL

yes

SQL-like query language

APIs and other access methods

CLI Client
JDBC
RESTful HTTP API

Proprietary protocol

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

Supported programming languages

Go
Java
JavaScript (Node.js)
Python
Rust

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

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

Server-side scripts

Stored procedures

JavaScript

Triggers

JavaScript

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

Implicit feature of the cloud service

Replication methods

Methods for redundantly storing data on multiple nodes

none

Repcached, a Memcached patch, provides this functionallity

yes

Implicit feature of the cloud service

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

Immediate Consistency

Bounded Staleness
Consistent Prefix
Eventual Consistency
Immediate Consistency

Consistency level configurable on request level
Session Consistency

Foreign keys

Referential integrity

Transaction concepts

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

yes

Multi-item ACID transactions with snapshot isolation within a partition

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

User concepts

Access control

Users with fine-grained authorization concept, user roles

yes

using SASL (Simple Authentication and Security Layer) protocol

Access rights can be defined down to the item level

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