Rockset raises $40 million to index and analyze data at scale

Real-time analytics startup Rockset today announced a $40 million round. The company says the funds will be used to grow its workforce and accelerate product development and research while bolstering its go-to-market efforts.

A 2018 report from Domo estimated that humans were creating 2.5 quintillion bytes (or 2.5 exabytes) of data per day, a number that has only increased since. Perhaps unsurprisingly, some companies are tapping the data deluge more effectively — and efficiently — than others. A recent Pricewaterhousecoopers survey of over 1,800 business leaders found that 43% obtained little tangible benefit from their information. And over 20% reported deriving no benefit whatsoever.

Rockset’s solution is a product suite that automatically indexes structured, semi-structured, geo, and time series data for real-time search and analytics. Using its tools, customers can create personalized experiences, build decision systems, and serve internet of things applications with an indexing database that powers fast queries.

Built by the creators of the open source RocksDB library, Rockset offers connectors that ingest data from MongoDB, DynamoDB, Kafka, Kinesis, Amazon Web Services, Google Cloud Platform, and more. All fields are entered into a converged index that includes an inverted index, a columnar index, and a row index, including deeply nested fields. This converged index compiles lists of information and allows analytical queries on datasets to expedite returns. Developers can run SQL queries — including filters, sorts, aggregations, and inner and outer joins — directly on semi-structured data.

Rockset recently launched Query Lambdas, which enables customers to build apps that consume data via an API. The company also kicked off support for self-driving deployments in virtual private clouds. The platform allows customers to select compute and storage independently. It also taps a cloud-native architecture that auto-scales and handles cluster provisioning and index management to optimize for cost. Rockset says all data is encrypted at rest and in transit, and it offers developers the option of masking sensitive data using field mappings at the time of ingest.

Danish financial services company Matter uses Rockset to run analytical queries on semi-structured data in Amazon S3 and DynamoDB as part of its natural language processing architecture. Rockset says Matter can tap new AI models and data fields via its custom tagging app without having to rebuild the surrounding infrastructure and correct bad predictions.

Rockset also claims it is seeing substantial growth as the pandemic spurs investment in digital services. The company says revenue grew 290% in the last quarter, while the aggregate number of queries executed on the platform increased by 313%. Rockset also says it added hundreds of new users. The company powers over 100 apps, with more than 300 developers at Standard Cognition, Bosch, Sequoia, and others using the company’s cloud services.

“Today, every company is a data company building modern data applications,” Rockset cofounder and CEO Venkat Venkataramani told VentureBeat via email. “The real-time data revolution is already underway, and we are thrilled to be at the forefront of it by making real-time analytics at cloud-scale fast and easy.”

Sequoia Capital led the oversubscribed series B round, with participation from Greylock Partners. Both firms contributed to the company’s seed and series A funding. Rockset emerged from stealth in November 2018 with a $21.5 million investment. The company is based in San Mateo, California and has 32 employees.

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