DBMS > Amazon Redshift vs. IBM Db2 warehouse vs. Memcached vs. Qdrant

System Properties Comparison Amazon Redshift vs. IBM Db2 warehouse vs. Memcached vs. Qdrant

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Editorial information provided by DB-Engines

Name

Description

Large scale data warehouse service for use with business intelligence tools

Cloud-based data warehousing service

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

A high-performance vector database with neural network or semantic-based matching

Primary database model

Relational DBMS

Key-value store

Vector DBMS

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

Score	16.88
Rank	#35	Overall
	#22	Relational DBMS

Score	1.37
Rank	#160	Overall
	#74	Relational DBMS

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

Score	1.28
Rank	#167	Overall
	#8	Vector DBMS

Website

aws.amazon.com/redshift

www.ibm.com/products/db2/warehouse

www.memcached.org

github.com/qdrant/qdrant
qdrant.tech

Technical documentation

docs.aws.amazon.com/redshift

github.com/memcached/memcached/wiki

qdrant.tech/documentation

Developer

Amazon (based on PostgreSQL)

IBM

Danga Interactive

originally developed by Brad Fitzpatrick for LiveJournal

Qdrant

Initial release

2012

2014

2003

2021

Current release

1.6.27, May 2024

License

Commercial or Open Source

commercial

Open Source

BSD license

Open Source

Apache Version 2.0

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

FreeBSD
Linux
OS X
Unix
Windows

Docker
Linux
macOS
Windows

Data scheme

yes

schema-free

Typing

predefined data types such as float or date

yes

Numbers, Strings, Geo, Boolean

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

Keywords, numberic ranges, geo, full-text

SQL

Support of SQL

yes

does not fully support an SQL-standard

yes

APIs and other access methods

JDBC
ODBC

.NET Client API
JDBC
ODBC
OLE DB

Proprietary protocol

gRPC
OpenAPI 3.0
RESTful HTTP/JSON API

OpenAPI 3.0

Supported programming languages

All languages supporting JDBC/ODBC

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

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

.Net
Go
Java
JavaScript (Node.js)
Python
Rust

Server-side scripts

Stored procedures

user defined functions

in Python

PL/SQL, SQL PL

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

yes

none

Repcached, a Memcached patch, provides this functionallity

Collection-level 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, tunable 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

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

yes

using SASL (Simple Authentication and Security Layer) protocol

Key-based authentication

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