DBMS > Apache Druid vs. KeyDB vs. MySQL vs. Qdrant

System Properties Comparison Apache Druid vs. KeyDB vs. MySQL vs. Qdrant

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Editorial information provided by DB-Engines

Name

Description

Open-source analytics data store designed for sub-second OLAP queries on high dimensionality and high cardinality data

An ultra-fast, open source Key-value store fully compatible with Redis API, modules, and protocols

Widely used open source RDBMS

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

Primary database model

Relational DBMS
Time Series DBMS

Key-value store

Relational DBMS

Key/Value like access via memcached API

Vector DBMS

Secondary database models

Document store
Spatial DBMS

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

Score	3.25
Rank	#90	Overall
	#47	Relational DBMS
	#7	Time Series DBMS

Score	0.70
Rank	#229	Overall
	#32	Key-value stores

Score	1061.34
Rank	#2	Overall
	#2	Relational DBMS

Score	1.28
Rank	#167	Overall
	#6	Vector DBMS

Website

druid.apache.org

github.com/Snapchat/KeyDB
keydb.dev

www.mysql.com

github.com/qdrant/qdrant
qdrant.tech

Technical documentation

druid.apache.org/docs/latest/design

docs.keydb.dev

dev.mysql.com/doc

qdrant.tech/documentation

Developer

Apache Software Foundation and contributors

EQ Alpha Technology Ltd.

Oracle

since 2010, originally MySQL AB, then Sun

Qdrant

Initial release

2012

2019

1995

2021

Current release

29.0.1, April 2024

8.4.0, April 2024

License

Commercial or Open Source

Open Source

Apache license v2

Open Source

BSD-3

Open Source

GPL version 2. Commercial licenses with extended functionallity are available

Open Source

Apache Version 2.0

Cloud-based only

Only available as a cloud service

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Implementation language

Java

C++

C and C++

Rust

Server operating systems

Linux
OS X
Unix

Linux

FreeBSD
Linux
OS X
Solaris
Windows

Docker
Linux
macOS
Windows

Data scheme

yes

schema-less columns are supported

schema-free

yes

schema-free

Typing

predefined data types such as float or date

yes

partial

Supported data types are strings, hashes, lists, sets and sorted sets, bit arrays, hyperloglogs and geospatial indexes

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.

yes

Secondary indexes

yes

by using the Redis Search module

yes

Keywords, numberic ranges, geo, full-text

SQL

Support of SQL

SQL for querying

yes

with proprietary extensions

APIs and other access methods

JDBC
RESTful HTTP/JSON API

Proprietary protocol

RESP - REdis Serialization Protoco

ADO.NET
JDBC
ODBC
Proprietary native API

gRPC
OpenAPI 3.0
RESTful HTTP/JSON API

OpenAPI 3.0

Supported programming languages

Clojure
JavaScript
PHP
Python
R
Ruby
Scala

C
C#
C++
Clojure
Crystal
D
Dart
Elixir
Erlang
Fancy
Go
Haskell
Haxe
Java
JavaScript (Node.js)
Lisp
Lua
MatLab
Objective-C
OCaml
Pascal
Perl
PHP
Prolog
Pure Data
Python
R
Rebol
Ruby
Rust
Scala
Scheme
Smalltalk
Swift
Tcl
Visual Basic

Ada
C
C#
C++
D
Delphi
Eiffel
Erlang
Haskell
Java
JavaScript (Node.js)
Objective-C
OCaml
Perl
PHP
Python
Ruby
Scheme
Tcl

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

Server-side scripts

Stored procedures

Lua

yes

proprietary syntax

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

manual/auto, time-based

Sharding

horizontal partitioning, sharding with MySQL Cluster or MySQL Fabric

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

yes, via HDFS, S3 or other storage engines

Multi-source replication
Source-replica replication

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
Strong eventual consistency with CRDTs

Immediate Consistency

Eventual Consistency, tunable consistency

Foreign keys

Referential integrity

yes

not for MyISAM storage engine

Transaction concepts

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

Optimistic locking, atomic execution of commands blocks and scripts

ACID

not for MyISAM storage engine

Concurrency

Support for concurrent manipulation of data

yes

table locks or row locks depending on storage engine

yes

Durability

Support for making data persistent

yes

Configurable mechanisms for persistency via snapshots and/or operations logs

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

RBAC using LDAP or Druid internals for users and groups for read/write by datasource and system

simple password-based access control and ACL

Users with fine-grained authorization concept

no user groups or roles

Key-based authentication

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