Data Streaming
Every minute of every day, the world produces an unimaginable amount of data, and it continues to increase at a remarkable pace. In order to keep up with current business requirements, companies in every sector are increasingly moving from batch processing to real-time data sources. Data streams can be processed, stored, analyzed, and acted upon as they are generated in real-time by using stream processing technology.
What streaming is?
The word "streaming" is used to describe constant, never-ending streams of data with no start or end, that provide a constant feed of information which can be used on without first downloading. How water flows over a river or stream is an easy analogy. The streams come from different sources and flow into a single, continuous, combined stream at varying speeds and volumes. Likewise, all types of sources, in different formats and sizes, produce data streams. They can all be aggregated from apps, networking devices, and server log files, to website operation, banking transactions, and location data to capture real-time information and analytics seamlessly from a single source of reality.
![Scalable and resilient technology]()
Scalable and resilient technology
Maintain uninterrupted streaming service and high output across embedded environments
![Captivating UX to draw and attract]()
Captivating UX to draw and attract
Investigate the challenges and advantages of users so that the interface can naturally be improved
![Superb mobile experience]()
Superb mobile experience
Deliver an experience that encourages customers to watch streaming on mobile devices
![Compliance with industry standards]()
Compliance with industry standards
RTSP, UDP, TCP and other widely accepted protocol standards ensures the quality delivered
![Lean development and continuous support]()
Lean development and continuous support
Strategize the company as we constantly deliver new features to achieve deliverables.
Real-Time Data Streaming Tools and Technologies
Managing with Apache Kafka
A powerful streaming infrastructure and tools for efficiently ingesting and processing streaming data are needed to extract insight from real-time data streams. Apache Kafka offers a high-scale, low-latency platform for handling database streaming for many organizations.
Although Kafka solves a number of problems associated with dealing with real-time data streams, it also has the potential to degrade source system efficiency and necessitate complex custom coding, placing a strain on limited IT resources. Zuccotech offers a powerful solution to overcome these challenges in order to allow businesses to easily process real-life data streams with Apache Kafka.
Universal and scalable streaming architecture
Enterprises can more efficiently consume and process vast volumes of data with superior and advanced streaming architectures while simplifying data stream processing management. Apache Kafka is a high-scale, low-latency platform that is becoming increasingly important in streaming architecture for a rising number of companies.
Kafka provides better capacity, allowing for more than 100,000 transactions per second. It easily scales with no downtime, is highly dependable, and delivers unrivaled efficiency. But the management of Kafka as a streaming architecture component will add a significant burden to IT teams. Data streaming into Kafka can necessitate comprehensive custom coding, and real-time data ingestion via Kafka can have a negative impact on source system performance.
Real Time Streaming Protocol
The Real-Time Streaming Protocol (RTSP), also known as the Presentation Control Protocol (PCP), is a ' +standard protocol for controlling the streaming of audio and video data over the internet. The technique known as real-time streaming, unlike the standard HTTP that uses a progressive technique, provides real-time streaming protocol with continuous streams of requested data without necessarily storing it on the hard disk.
Thereby acting as a 'remote control' making the flow on demand. Real-time streaming protocol incorporates TCP (connection-based protocol), UDP (connectionless protocol), and RTP to accomplish a variety of functions by maintaining a session/state between the server and the client via an identifier. In other words, by choosing the right delivery method, the RTSP server and client can simultaneously send requests, a gain over other protocol types.