The Indian multinational online car marketplace Cars24 serves 300 million users globally. The company offers services that span sales, insurance, maintenance, financing, and more, reshaping the entire car ownership journey.

Speaking at MongoDB .local Bengaluru in July 2025, Pradeep Sharma, Head of Technology at Cars24, shared how MongoDB has been a key driver of Car24’s digital transformation journey. Specifically, he highlighted two recent use cases that show how MongoDB Atlas has helped Cars24 scale, improve its search capabilities, and reduce its architectural complexity.

Matching the growing scale with simplified and expanded search

Cars24 has operations in multiple countries, and a diverse customer base. Over the years, the company has used customer data, behavior analytics, and operational workflows to build, evolving from being a platform for buying and selling cars, to an end-to-end ecosystem, supported by a hub of interconnected systems.

At the start of its journey, Cars24 relied on legacy databases for managing and searching data, such as Postgres. Their relational database set-up would store information, synchronize the data to a separate “bolt-on” search engine (such as Elasticsearch), manually indexing it, and then querying the index.

While initially effective for a small application ecosystem, these processes became bottlenecked as the organization’s services grew. Multiple engineering teams piped data into a single search index, which often resulted in synchronization challenges and overwhelming administrative overhead.

Cars24 faced three core limitations with this setup:

Lower developer productivity: Exponential effort was spent maintaining pipelines and synchronizing procedures. Developers had little bandwidth for building business features or innovation.
Architectural complexity: Ensuring data sync consistency required multiple pipelines and race logic. This led to inefficiencies in real-time dashboard updates for agents.
Operational overhead: Maintaining separate systems for database and search—alongside provisioning, patching, scaling, and monitoring—strained resources.

Seeking an integrated approach, Cars24 embraced MongoDB Atlas, hosted on Google Cloud. MongoDB Atlas would serve as a single, consistent, modern database and embedded search solution, powered by Apache Lucene.

MongoDB Atlas Search also enabled Cars24 to run queries directly in the database. This eliminated the need to synchronise data between systems while delivering real-time results.

This unified approach allowed the company’s developers to transition from managing complex synchronization mechanisms to building applications. Furthermore, the reduced administrative overhead enabled Cars24 to consolidate the team’s efforts, and to streamline query execution across the ecosystem.

Thanks to MongoDB Atlas and MongoDB Atlas Search, Cars24 was able to:

Avoid "synchronization tax”: Switching to MongoDB Atlas eliminated the need for data synchronization and the additional tooling this mandated. Real-time searches can be performed from a single interface and workflow.
Deliver new search features faster: By using a single, unified API across database and search operations, new features can be delivered rapidly.
Work with a fully managed platform: With MongoDB Atlas, Cars24’s engineers can focus more on application development and building products, rather than thinking about managing indexes, syncing, and more.

Following this successful migration, Cars24 decided to also use MongoDB Atlas to replace one of its legacy databases, ArangoDB. The switch to MongoDB Atlas eliminated major roadblocks for other critical search capabilities.

From ArangoDB to MongoDB: Streamlined operations and 50% cost savings

As Cars24 scaled new services globally, it encountered limitations with its geospatial search solution, which was based on ArangoDB. This included performance bottlenecks, weak transactions as it was difficult to guarantee consistent data operations, and a limited ecosystem which meant that scaling developer onboarding and troubleshooting became increasingly onerous.
Moving to MongoDB Atlas enabled Cars24 to transition its geospatial services, consolidating its data storage and search capabilities under a single, versatile platform.

“We now have a highly available architecture, and an amazing team at MongoDB that has our back,” said Sharma.

MongoDB offered a proven architecture for high availability, scalability, and real-world production readiness:

Enhanced scalability: MongoDB’s ability to scale massive workloads supports Cars24’s growing global presence.
Reliable transactions: MongoDB provides robust multi-document ACID transactions across shards, meeting mission-critical needs.
Streamlined operations: MongoDB offers a single platform that is not limited to a database only. By consolidating its geospatial search workload under MongoDB, Cars24 has reduced maintenance and operational overhead.

Not only did Cars24 cut costs in half by moving to MongoDB, but the widespread market adoption of MongoDB Atlas also means that Cars24 can continue to rapidly onboard developers familiar with MongoDB, a recruiting priority for Cars24’s growing development team.

“To give you an idea, one of our business units had a developer team of less than 10 about a year ago. Now they are a triple-digit team,” said Sharma. “If we are going to keep introducing new developers, for a product coming up or scaling up, it becomes very important to focus on the community skills and support provided by our technology partner.”

“Now that we have moved from ArangoDB to MongoDB Atlas, our developers are the happiest,” he added.

Cars24 is now looking to consolidate even more of its application and data workflows under MongoDB Atlas. With the growing number of developers joining Cars24’s engineering teams, plans are to utilize MongoDB Atlas further to enhance productivity, scalability, and data-driven insights.

Visit the MongoDB Atlas Learning Hub to learn more about Atlas.

To learn more about MongoDB Atlas Search, visit our product page.

专题：database_scaling

Cars24通过MongoDB Atlas优化搜索系统与全球业务扩展