MindOrigin is Revolutionizing How India Analyzes Stock Market Data with MongoDB Time Series Collections

In India’s fast-evolving financial sector, MindOrigin has quickly established itself as a prominent provider of real-time stock data. Founded in 2023, MindOrigin powers analysis for retail and institutional investors alike with their investment platform. The growth of these platforms makes investing accessible to millions of Indians, reflecting a broader shift in India’s financial ecosystem, in which data access and transparency are critical to success.

As a B2B product, MindOrigin’s investment platform responds to this demand for real-time insights by aggregating and processing up to 54 million transactions per hour. The platform empowers clients to analyze essential metrics (such as Open-High-Low-Close (OHLC) values), spot trends, and rapidly respond to corporate actions like stock splits and bonus issues.

Operating in India’s stock market—the fifth-largest globally by market cap—MindOrigin serves clients who demand fast, high-performance data analytics. To meet these needs, MindOrigin required a platform that could scale with surging data volumes and comply with Indian data residency laws, ensuring that financial data remains within the country.

MindOrigin identified MongoDB Atlas, equipped with native time series collections, as the perfect fit for the company’s requirements. By deploying MongoDB Atlas, MindOrigin achieved significant performance gains while cutting storage costs by 70%. This combination of speed and cost efficiency has enhanced their ability to deliver actionable insights and positioned them as a leader in India’s rapidly evolving investment landscape. This streamlined approach enables MindOrigin to provide compliant, scalable, and high-speed data operations ready for current and future demands.

Prajwal Somashekara, CEO, MindOrigin

India's two major stock exchanges, the NSE and BSE, handle an astounding 15,000 transactions per second, producing 54 GB of data and 324 million transactions each trading day. MindOrigin’s original legacy architecture relied on PostgreSQL with TimescaleDB. This struggled to keep up with the high-performance and scalability demands essential for real-time financial data processing. Traders and analysts using MindOrigin required the flexibility to perform ad hoc queries across various timeframes—from milliseconds to weeks. However, PostgreSQL’s architecture could not deliver the necessary response times. This query latency impacted clients' ability to make timely, informed decisions.

Another challenge stemmed from handling complex corporate actions, such as stock splits and bonus issues, which are common in the Indian market. These actions necessitate recalculating historical prices to ensure accuracy—a task that took PostgreSQL up to two hours to process. These delays hindered timely data updates, which are essential for delivering accurate financial insights. Furthermore, regulatory compliance standards mandated that all financial data be stored in the country. MindOrigin required a database capable of scaling to manage large volumes of data in cloud regions within India, while supporting adherence to local data residency requirements. To address these challenges and to maintain a competitive edge, MindOrigin determined MongoDB Atlas was the only suitable database solution for its needs.

MindOrigin’s migration to MongoDB Atlas with time series collections led to a transformative shift in how the company’s data was managed and processed. MongoDB Atlas’s time series-specific capabilities delivered an optimized, flexible data model tailored to handle time-stamped data like OHLC values. By structuring data in this way, MindOrigin could run complex queries and anticipate response times to meet the demands of their high-frequency, data-intensive workloads.

Faced with the need for a more flexible and high-performing database solution, MindOrigin turned to MongoDB Atlas. The migration process was remarkably swift—within just one week, they fully implemented MongoDB Atlas. To meet data residency requirements, they deployed clusters in India, ensuring compliance and safeguarding data privacy.

MongoDB time series collections enabled MindOrigin’s clients to instantly access data across customized timeframes. As Prajwal Somashekara, CEO at MindOrigin, noted, “MongoDB’s time series collections allow us to meet the speed and data integrity standards required by modern financial markets.” Additionally, the platform’s flexible aggregation framework simplified the recalculation process for corporate actions. This makes it easy to adjust historical data for events like stock splits and bonus issues with zero delay. This level of agility enabled MindOrigin to keep its data accurate and up-to-date, meeting its clients’ need for real-time insights.

With MongoDB Atlas’s querying capabilities, the investment platform now delivers traders and analysts seamless access to both raw and aggregated data, tailored precisely to their time-based needs. This infrastructure enabled MindOrigin to ensure the high-performance experience their clients expect while freeing their backend engineering team from the complexities of managing compliance and infrastructure.

Prajwal Somashekara, CEO, MindOrigin

Since moving to MongoDB Atlas with time series collections, MindOrigin has experienced substantial improvements in data handling and overall business efficiency. MongoDB’s time series collections leverage block-processing for enhanced query performance on time-stamped data, which has accelerated MindOrigin’s data querying processes by an impressive 15x. This gives clients near-instant access to insights crucial for high-frequency trading. Moreover, the time series collections advanced storage compression has reduced storage costs by 70%, significantly lowering operational expenses without compromising data availability.

Beyond these tangible benefits, MongoDB Atlas’s global availability has proven invaluable for compliance adherence. By deploying clusters in India, MindOrigin adheres to data residency laws while achieving the scalability required to meet the Indian stock exchange's growing data demands. “With MongoDB Atlas our team can focus on market opportunities rather than infrastructure and compliance, thanks to its unified, secure architecture,” Somashekara emphasized.

MindOrigin’s adoption of MongoDB Atlas has empowered the delivery of faster, more reliable data access to clients in India’s high-stakes financial sector. The efficiency and scalability of MongoDB Atlas have positioned MindOrigin to serve a growing client base, which is fueling MindOrigin’s continued leadership in a market that thrives on real-time insights and rapid adaptability.