Send Data to Qdrant on Qdrant - Vector Database

Databricks Ingestion

info@qdrant.tech (Andrey Vasnetsov) — Mon, 01 Jan 0001 00:00:00 +0000

Ingest Databricks Data into Qdrant

Time: 30 min	Level: Intermediate	Complete Notebook

Databricks is a unified analytics platform for working with big data and AI. It’s built around Apache Spark, a powerful open-source distributed computing system well-suited for processing large-scale datasets and performing complex analytics tasks.

Apache Spark is designed to scale horizontally, meaning it can handle expensive operations like generating vector embeddings by distributing computation across a cluster of machines. This scalability is crucial when dealing with large datasets.

Querying with Airflow

info@qdrant.tech (Andrey Vasnetsov) — Mon, 01 Jan 0001 00:00:00 +0000

Qdrant Semantic Querying with Airflow and Astronomer

Time: 45 min	Level: Intermediate

In this tutorial, you will use Qdrant as a provider in Apache Airflow, an open-source tool that lets you setup data-engineering workflows.

You will write the pipeline as a DAG (Directed Acyclic Graph) in Python. With this, you can leverage the powerful suite of Python’s capabilities and libraries to achieve almost anything your data pipeline needs.

Kafka Streaming into Qdrant

info@qdrant.tech (Andrey Vasnetsov) — Mon, 01 Jan 0001 00:00:00 +0000

Stream Real-Time Data into Qdrant with Kafka and Confluent

Author: M K Pavan Kumar , research scholar at IIITDM, Kurnool. Specialist in hallucination mitigation techniques and RAG methodologies. • GitHub • Medium

Introduction

This guide will walk you through the detailed steps of installing and setting up the Qdrant Sink Connector, building the necessary infrastructure, and creating a practical playground application. By the end of this article, you will have a deep understanding of how to leverage this powerful integration to streamline your data workflows, ultimately enhancing the performance and capabilities of your data-driven real-time semantic search and RAG applications.