Swiggy, Jio, and the Push for Instant Data: Confluent’s Role in a Changing Market

The ability to process and act on live data is no longer a luxury—it’s a necessity in today’s AI-powered world. Companies like Swiggy, Jio Platforms, and Databricks are leveraging Confluent’s real-time data streaming technology to improve customer experiences, optimize operations, and unlock new levels of efficiency.

In this exclusive interview, Rubal Sahni, Area Vice President & Country Manager, Confluent India, shares how Confluent is shaping the future of data infrastructure in India, driving AI-led innovation, and ensuring businesses stay ahead in an increasingly competitive digital landscape.

How does the Swiggy partnership, alongside your recent collaborations with Jio Platforms and Databricks, strategically position Confluent within the rapidly evolving Indian cloud data streaming and AI ecosystem?

These recent moves place Confluent at the heart of three key trends shaping India’s tech landscape: real-time data processing, cloud computing, and AI development. 

Our work with Swiggy highlights how data streaming supports a major consumer platform—one that’s handled over three billion orders across 680 cities.

As a leader in hyperlocal commerce, Swiggy showcases how real-time insights can keep a massive, customer-focused operation running smoothly. It’s a practical example for any business juggling scale and speed in today’s market.

Our partnership with Jio Platforms Limited will advance India’s digital capabilities further with the integration of Confluent Cloud into Jio Cloud Services—the first data streaming platform to do so.

Jio’s reach in India’s digital ecosystem is unmatched, and this collaboration makes it simpler for businesses of all sizes, including public sector organizations, to tap into real-time data capabilities. It delivers enterprise-grade security and governance, meeting the needs of a market eager to get started with data streaming while ensuring trusted, secure data at extremely large scales.

The collaboration with Databricks addresses a common pain point: the disconnect between operational systems where data is generated and analytical systems where that data is turned into insights.

Enterprises often struggle to turn live data into actionable AI insights because these worlds exist in separate silos with different teams, tools and processes.

By linking our streaming platform with Databricks’ Data Intelligence Platform, we’re helping to bridge that gap, enabling companies to build AI applications with real-time data that is discoverable, secure and trustworthy. 

How specifically does Confluent's platform enable Swiggy to achieve real-time decision-making at the scale of billions of orders, and what are some concrete examples of these decisions?

Swiggy’s operation is enormous—over three billion orders across 680 cities—and our platform is used for real-time predictions, recommendations, analytics, and more.

They used to rely on open-source Apache Kafka, which got the job done but required constant upkeep. Switching to our fully managed Confluent Cloud setup changed that. 

It freed their data team from tinkering with infrastructure, letting them shift focus to the business side of things rather than just maintaining systems.

One example is the predicted SLA customers see in the app.

When someone orders groceries and wonders, “How long will this take?” 

Our platform pulls live data from restaurants, delivery partners, and traffic conditions, then calculates a predicted delivery time based on their location. Apache Flink powers this by processing data as it streams in—no waiting for batches—so the answer pops up instantly. 

During peak times, like festival seasons when orders flood in, our elastic scaling steps up. Swiggy’s team no longer has to manually adjust capacity—they set their needs once, and we handle the rest, ensuring service doesn’t falter under pressure. 

We also help them track how data flows between systems, spotting inefficiencies like duplicate steps and smoothing out workflows. This cuts unnecessary delays across their network of customers, restaurants, and partners, creating a robust foundation for quick, smart decisions that scale with their growth.

Explain the technical mechanisms behind how Confluent's asynchronous data streaming contributes to Swiggy's precise delivery time calculations.

Swiggy’s ability to give customers pinpoint delivery times relies on our asynchronous data streaming approach. Unlike batch processing, our platform lets information move independently.

When a customer checks their ETA, data streams in from different sources all at once. Our platform gathers these events as they happen, without holding up the process for any single piece to complete.

From there, the Apache Flink service takes over, processing these streams in real-time. It pulls together all the variables and crunches them into an accurate delivery estimate on the spot.

The pre-built connectors we provide make this smooth, linking Swiggy’s varied systems without forcing them to build custom integrations from scratch. That means every component affecting delivery gets factored in quickly and reliably.

We also give Swiggy a clear view of how data flows between their systems. This mapping helps them spot any hiccups—like a sluggish feed slowing down the pipeline—and fix them fast. It’s all about keeping the process flexible and responsive, so customers get a delivery time they can trust, updated the moment something shifts.

How does Confluent's platform ensure seamless service during Swiggy's peak order surges through elastic scaling, and what are the key triggers for this scaling?

Swiggy operates at the intersection of e-commerce and logistics, where customers demand fast, reliable services. And these expectations especially skyrocket during peak demand—like India’s festival seasons. 

With billions of orders flowing across 680 cities, any bottleneck in data processing could disrupt their hyperlocal delivery network, impacting end-user experience.

Our elastic scaling capability addresses this by dynamically adjusting resources to match real-time load, ensuring Swiggy’s systems stay responsive under pressure.

The platform delivers this through automated, cloud-native scaling that removes the manual burden Swiggy once faced with their open-source Kafka setup. Engineers no longer need to reactively provision servers—they set throughput targets once, and Confluent Cloud adjusts compute and storage with a single configuration update. This scaling responds to specific triggers woven into the system. For anticipated spikes, like festivals, Swiggy can preemptively boost capacity using historical order trends.  

Unpredictable surges—part of Swiggy’s fast-moving business—are handled by the system’s inherent elasticity, adapting to sudden jumps in load. And when cluster health falters, the platform quickly adapts to maintain uptime. This automation keeps Swiggy’s service seamless, letting their data team focus on refining operations rather than wrestling with infrastructure.

While the official impact announcement is on March 4th, can you provide a brief glimpse into the key metrics that demonstrate the success of this partnership?

By shifting from open-source Kafka to our managed Confluent Cloud service, we’ve boosted efficiency and cut latencies in critical workflows, freeing Swiggy’s data team from maintenance tasks to focus on refining operations for their billions of orders.

This real-time streaming has also sharpened delivery ETAs, optimizing customer wait times and enabling more personalized interactions through tailored updates—that can lift engagement and retention.

On the resilience front, the system’s dynamic scaling keeps Swiggy steady under pressure, adapting resources seamlessly to handle peak loads.

How has the implementation of Confluent's platform directly improved the end-user experience for Swiggy customers?

Confluent’s platform powers Swiggy with real-time data streaming to calculate precise delivery ETAs, pulling live inputs like traffic conditions, restaurant prep times, and rider locations with Apache Flink. These estimates update instantly as conditions shift, while our pre-built connectors ensure seamless integration across Swiggy’s ecosystem. During peak demand, like festival surges, our elastic scaling adjusts resources automatically to prevent order backups, maintaining smooth service across 680 cities. 

This all ties into what customers expect in 2025—especially in a fast-moving industry like on-demand delivery where Swiggy operates. Today’s consumers, shaped by a digital-first world, demand more than speed; they want predictability and clarity. They expect to know exactly when their order will arrive, with no guesswork or delays, and trust hinges on that precision.

By enabling Swiggy to deliver accurate ETAs, hassle-free tracking, and reliable service even under pressure, we’re meeting those needs, making every interaction smoother and more delightful for a modern audience that values certainty as much as convenience.

What specific data workflow and governance challenges faced by Swiggy has Confluent solved?

Confluent’s platform tackles data workflow and governance challenges for Swiggy by enabling smoother operations and stronger oversight. We streamline workflows by automating the heavy lifting of data management—think processing streams and connecting systems—freeing up teams to optimize rather than just maintain. Our tools integrate disparate data sources seamlessly, ensuring information moves efficiently across the operation without manual stitching.

For governance, we bolster control with centralized mechanisms that maintain data integrity and enforce standards, simplifying what can be a tangled mess in large-scale setups.

This matters in 2025, especially for a delivery leader like Swiggy, where customers expect precision and reliability at every step. The modern consumer wants fast, consistent service, and that hinges on a business keeping its data house in order—workflows that don’t stumble and governance that builds trust.

By providing a robust framework for both, we help Swiggy manage its complex ecosystem, ensuring it can meet those demands with data that’s both fluid and dependable.

How can the solution that was implemented scale to meet Swiggy's future projected growth?

Confluent sets a strong base for companies like Swiggy to scale up, handling the massive data loads that come with growth in a way that unlocks real potential. Businesses at this level churn out enormous amounts of data—orders, locations, customer preferences—and that pile keeps growing as they expand.

Our platform takes that raw volume and turns it into something usable, with scalable processing that keeps pace with rising demand and tools to manage complexity without breaking down. It’s about enabling these companies to sift through the chaos, spot patterns, and act fast—whether that’s optimizing delivery routes, personalizing offers, or entering new markets.

That scalability is critical in 2025, where industries thrive on speed and reach. Modern consumers expect instant, reliable delivery, and businesses need systems that grow without friction. With our platform, Swiggy has a foundation that supports more orders, wider coverage, and richer experiences—meeting the rising bar of customer demand while staying efficient and trusted.