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Connect Kafka to Apache Druid

Quix helps you integrate Apache Kafka with Apache Druid using pure Python.

Transform and pre-process data, with the new alternative to Confluent Kafka Connect, before loading it into a specific format, simplifying data lake house architecture, reducing storage and ownership costs and enabling data teams to achieve success for your business.

Apache Druid

Apache Druid is a high-performance, real-time analytics database designed for fast, interactive analytics on large datasets. It provides low-latency queries and scalable data ingestion, allowing users to explore, analyze, and visualize their data in real-time. With its column-oriented storage, Druid enables users to aggregate, filter, and drill down into data with ease. Its distributed architecture ensures high availability and fault tolerance for mission-critical applications, making it a popular choice for companies looking to gain insights from their data quickly and efficiently.

Integrations

Quix is a good fit for integrating with Apache Druid due to its ability to pre-process and transform data from various sources before loading it into a specific data format, simplifying lakehouse architecture with customizable connectors for different destinations. Additionally, Quix Streams, an open-source Python library, facilitates the transformation of data using streaming DataFrames, supporting operations like aggregation, filtering, and merging during the transformation process. The platform ensures efficient data handling from source to destination with no throughput limits, automatic backpressure management, and checkpointing. Quix also supports sinking transformed data to cloud storage in a specific format, ensuring seamless integration and storage efficiency at the destination. Furthermore, it offers a cost-effective solution for managing data from source through transformation to destination, compared to other alternatives.