Can Kafka be used for video streaming?

This project serves as a lightweight demo for a video streaming pipeline. You shouldn't use this project in a production environment, but it's a nice way to get you started with Kafka, Flask, and the ML libs, all using Python.

Can Kafka be used as storage?

Kafka as a Datastore. Kafka can be used for storing data. You may be wondering whether Kafka is a relational or NoSQL database. The answer is that it is neither one nor the other.
Is Kafka good for real-time?
Kafka is real-time! Kafka provides capabilities to process trillions of events per day. Each Kafka broker (= server) can process tens of thousands of messages per second. End-to-end latency from producer to consumer can be as low as ~10ms if the hardware and network setup are good enough.
How Kafka is used in Netflix?
It enables applications to publish or subscribe to data or event streams. It stores data records accurately and is highly fault-tolerant. It is capable of real-time, high-volume data processing. It is able to take in and process trillions of data records per day, without any performance issues.

Can Kafka be used for audio streaming?

The Kafka Streams Quick Start demonstrates how to run your first Java application that uses the Kafka Streams library by showcasing a simple end-to-end data pipeline powered by Kafka. Streaming Audio is a podcast from Confluent, the team that built Kafka.

What is Kafka not good for?

This one is pretty straightforward and related to the above section. Kafka is not a deterministic system. Safety-critical applications cannot use it for a car engine control system, a medical system such as a heart pacemaker, or an industrial process controller.
What can Kafka be used for?
Kafka is primarily used to build real-time streaming data pipelines and applications that adapt to the data streams. It combines messaging, storage, and stream processing to allow storage and analysis of both historical and real-time data.
Does uber use Kafka?
Background. Uber has one of the largest deployments of Apache Kafka® in the world. It empowers a large number of real-time workflows at Uber, including pub-sub message buses for passing event data from the rider and driver apps, as well as financial transaction events between the backend services.
Apache Flink is a stream processing framework that can be used easily with Java. Apache Kafka is a distributed stream processing system supporting high fault-tolerance.
Kafka is Highly Reliable. Kafka replicates data and is able to support multiple subscribers. Additionally, it automatically balances consumers in the event of failure. That means that it's more reliable than similar messaging services available.
Is Kafka good for ETL?
Companies use Kafka for many applications (real time stream processing, data synchronization, messaging, and more), but one of the most popular applications is ETL pipelines. Kafka is a perfect tool for building data pipelines: it's reliable, scalable, and efficient.
Why is Kafka better than ETL?
Stream processing and transformations can be implemented using the Kafka Streams API — this provides the T in ETL. Using Kafka as a streaming platform eliminates the need to create (potentially duplicate) bespoke extract, transform, and load components for each destination sink, data store, or system.

Can I use Kafka as database?

The main idea behind Kafka is to continuously process streaming data; with additional options to query stored data. Kafka is good enough as a database for some use cases. However, the query capabilities of Kafka are not good enough for some other use cases.