DataStax Astra DB: The Catalyst Behind Chingari's Phenomenal Social Media Journey and Real-time AI Initiatives
In the fast-paced, crowded social media universe, innovation is how you stand out. Chingari, one of India's fastest-growing social media apps with over 175 million users, has revolutionized how creators and viewers monetize their content and time. Learn how Astra DB has been instrumental in tackling the challenges associated with real-time data.
- Enhanced developer efficiency and productivity without database troubleshooting.
- Significant cost savings (estimated at approximately 70%) compared to other database options over three years.
- Easy setup and quick deployment save time and resources on maintaining an in-house database cluster.
- Able to query millions of records within milliseconds, providing exceptional support for localization initiatives.
Chingari is a rapidly growing social media app that provides users with a platform to create short-form and long-form content, including live-streaming audio. Chingari's true potential lies in its decentralized nature and the incentivization it offers to its creators and users. However, the platform faces several challenges that need to be addressed for sustained growth.
Chingari faces the critical challenge of managing a vast amount of real-time data from its 175 million users. The social media platform uses a recommendation engine to personalize user experiences and deliver relevant content. However, accurately tracking and calculating user contributions in real-time, including commenting, video watching, and live streaming participation, presents a significant obstacle. Furthermore, as Chingari expands globally and focuses on supporting local languages, efficient data management becomes essential for the company's growth and success.
Astra DB, DataStax’s popular pay-as-you-go database-as-a-service (DBaaS) built on the open source Apache Cassandra® is a powerful component of Chingari’s data infrastructure. With Astra DB, Chingari can process large-scale data and run algorithms on top of it to reward users based on their contributions in near real-time. The serverless model provided by DataStax enables Chingari to scale up and handle spikes in traffic seamlessly. This partnership has significantly improved Chingari's ability to handle data processing and focus on application growth.
Chingari's real-time recommendation system is vital to user retention. The system quickly analyzes user preferences based on their interactions with the app, enabling Chingari to provide tailored recommendations within the first few video views. Machine learning models promptly process and categorize uploaded content, ensuring it reaches users immediately. Astra DB has enabled fast and efficient data processing, resulting in a better user experience.
Kamal Sain, VP of Engineering at Chingari, said, “Astra DB and DataStax have now resolved the problem we had with the real-time data. We can now focus on growing our application at scale.”
Chingari's developers no longer need to spend time troubleshooting database-related issues. The resulting improvements in productivity allow developers to focus on other critical activities rather than worrying about database performance and monitoring. Chingari anticipates significant cost savings over a three-year period by utilizing DataStax compared to other database options. The ability to quickly set up and deploy with DataStax has been invaluable, as it saves considerable time and resources that would otherwise be spent on setting up and maintaining an in-house database cluster.
“Based on our calculations, we anticipate saving approximately 70% of costs over a three-year period compared to using other databases if we had not chosen DataStax. This significant cost reduction is a substantial benefit for startups like ours,” said Shavinder Singh, Head Of Engineering at Chingari. “Overall, performance and latency are crucial for any social media application. In our mining reward program, we have achieved less than one millisecond latencies, significantly impacting the user experience.”
Chingari plans to integrate Astra DB extensively throughout the app for its mining and rewards program, the chat feature, and the recommendation systems for audio and live rooms, which will require vector search, now supported in Astra DB.
Vector search is a key capability for letting databases provide long-term memory for AI applications using large language models (LLMs) and other AI use cases. The availability of this new tool in Astra DB will enable developers to easily leverage the massively scalable Cassandra database for their LLM, AI assistant, and real-time generative AI projects.
As Chingari continues its remarkable growth trajectory, it aims to expand globally and support local languages through localization efforts. “Astra DB enables us to query millions of records within milliseconds, providing exceptional support for our localization initiatives. This partnership is instrumental in helping us achieve our goals, particularly with their real-time AI platform,” said Biswatma Nayak, Chingari’s CTO, and co-founder.
Chingari has achieved impressive user engagement, developer productivity, and cost savings with Astra DB. The seamless integration and powerful features offered by Astra DB have positioned Chingari as a leading player in the social media space, enabling the platform to provide a rewarding and immersive experience to both creators and users.