DBMS > Qdrant vs. RocksDB vs. STSdb vs. WakandaDB

System Properties Comparison Qdrant vs. RocksDB vs. STSdb vs. WakandaDB

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Editorial information provided by DB-Engines

Name

Description

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

Embeddable persistent key-value store optimized for fast storage (flash and RAM)

Key-Value Store with special method for indexing

optimized for high performance using a special indexing method

WakandaDB is embedded in a server that provides a REST API and a server-side javascript engine to access data

Primary database model

Vector DBMS

Key-value store

Object oriented DBMS

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

Score	1.28
Rank	#167	Overall
	#6	Vector DBMS

Score	3.41
Rank	#86	Overall
	#11	Key-value stores

Score	0.10
Rank	#357	Overall
	#51	Key-value stores

Score	0.10
Rank	#356	Overall
	#16	Object oriented DBMS

Website

github.com/qdrant/qdrant
qdrant.tech

rocksdb.org

github.com/STSSoft/STSdb4

wakanda.github.io

Technical documentation

qdrant.tech/documentation

github.com/facebook/rocksdb/wiki

wakanda.github.io/doc

Developer

Qdrant

Facebook, Inc.

STS Soft SC

Wakanda SAS

Initial release

2021

2013

2011

2012

Current release

9.2.1, May 2024

4.0.8, September 2015

2.7.0 (April 29, 2019), April 2019

License

Commercial or Open Source

Open Source

Apache Version 2.0

Open Source

BSD

Open Source

GPLv2, commercial license available

Open Source

AGPLv3, extended commercial license available

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

Providers of DBaaS offerings, please contact us to be listed.

Implementation language

Rust

C++

C++, JavaScript

Server operating systems

Docker
Linux
macOS
Windows

Linux

Windows

Linux
OS X
Windows

Data scheme

schema-free

yes

Typing

predefined data types such as float or date

Numbers, Strings, Geo, Boolean

yes

primitive types and user defined types (classes)

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

yes

Keywords, numberic ranges, geo, full-text

SQL

Support of SQL

APIs and other access methods

gRPC
OpenAPI 3.0
RESTful HTTP/JSON API

OpenAPI 3.0

C++ API
Java API

.NET Client API

RESTful HTTP API

Supported programming languages

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

C
C++
Go
Java
Perl
Python
Ruby

C#
Java

JavaScript

Server-side scripts

Stored procedures

yes

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

horizontal partitioning

none

Replication methods

Methods for redundantly storing data on multiple nodes

Collection-level replication

yes

none

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency, tunable consistency

Immediate Consistency

Foreign keys

Referential integrity

Transaction concepts

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

yes

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

Key-based authentication

yes

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