DBMS > Qdrant vs. WakandaDB vs. Weaviate

System Properties Comparison Qdrant vs. WakandaDB vs. Weaviate

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Editorial information provided by DB-Engines

Name

Description

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

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

An AI-native realtime vector database engine that integrates scalable machine learning models.

Primary database model

Vector DBMS

Object oriented DBMS

Vector DBMS

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

Score	1.93
Rank	#121	Overall
	#9	Vector DBMS

Score	0.03
Rank	#359	Overall
	#17	Object oriented DBMS

Score	1.50
Rank	#142	Overall
	#10	Vector DBMS

Website

github.com/qdrant/qdrant
qdrant.tech

wakanda.github.io

github.com/weaviate/weaviate
weaviate.io

Technical documentation

qdrant.tech/documentation

wakanda.github.io/doc

weaviate.io/developers/weaviate

Developer

Qdrant

Wakanda SAS

Weaviate B.V.

Initial release

2021

2012

2019

Current release

2.7.0 (April 29, 2019), April 2019

1.19, May 2023

License

Commercial or Open Source

Open Source

Apache Version 2.0

Open Source

AGPLv3, extended commercial license available

Open Source

commercial license available with Weaviate Enterprise

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++, JavaScript

Server operating systems

Docker
Linux
macOS
Windows

Linux
OS X
Windows

Data scheme

schema-free

yes

yes, maps to GraphQL interface

Typing

predefined data types such as float or date

Numbers, Strings, Geo, Boolean

yes

string, int, float, geo point, date, cross reference, fuzzy references

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

yes

all data objects are indexed in a semantic vector space (the Contextionary), all primitive fields are indexed

SQL

Support of SQL

GraphQL is used as query language

APIs and other access methods

gRPC
OpenAPI 3.0
RESTful HTTP/JSON API

OpenAPI 3.0

RESTful HTTP API

GraphQL query language
RESTful HTTP/JSON API

Supported programming languages

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

JavaScript

JavaScript / TypeScript
Python

Server-side scripts

Stored procedures

yes

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

Collection-level replication

none

yes

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

Eventual Consistency

Foreign keys

Referential integrity

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

Key-based authentication

yes

API Keys
OpenID Connect Discovery

More information provided by the system vendor

Specific characteristics

Weaviate is an open source vector database that is robust, scalable, cloud-native,...
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Competitive advantages

Flexible deployment - Free, open source or fully-managed cloud vector database service...
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Typical application scenarios

As a database supporting the development of generative AI and semantic search applications...
» more

Key customers

All companies that have data.
» more

Market metrics

As of mid 2023: Over 2 million open source downloads 3500+ Weaviate Slack community...
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Licensing and pricing models

Weaviate is open-source, and free to use. Weaviate is also available as a fully managed...
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and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.

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More resources

DB-Engines blog posts

Weaviate, an ANN Database with CRUD support
2 February 2021, Etienne Dilocker, SeMI Technologies (sponsor)

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Recent citations in the news

Qdrant review: A highly flexible option for vector search
29 July 2024, InfoWorld

Qdrant Launches Groundbreaking Pure Vector-Based Hybrid Search, Setting Higher Standards for RAG and AI Applications
2 July 2024, Business Wire

Build your First RAG with Qdrant
17 October 2024, packtpub.com

Vector database company Qdrant wants RAG to be more cost-effective
2 July 2024, VentureBeat

Qdrant unveils hybrid vector algorithm for improved RAG
2 July 2024, Blocks and Files

provided by Google News

Database company Weaviate speeds up AI development with flexible vector embeddings service
3 December 2024, SiliconANGLE News

Weaviate launches vector embeddings generation service
3 December 2024, Blocks and Files

Weaviate Achieves Amazon Web Services GenAI Competency Status
8 July 2024, GlobeNewswire

Weaviate launches flexible embedding service for AI development
10 December 2024, SDxCentral

StructuredRAG Released by Weaviate: A Comprehensive Benchmark to Evaluate Large Language Models’ Ability to Generate Reliable JSON Outputs for Complex AI Systems
26 August 2024, MarkTechPost

provided by Google News

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