Streaming data processing platform RisingWave lands $36M to launch a cloud service • ProWellTech

RisingWave Labs, a company developing a platform for data stream processing, today announced that it raised $36 million in a Series A funding round led by Yunqi Partners, undisclosed corporate investors and angel investors. Bringing RisingWave’s total raised to over $40 million, the capital will be put toward scaling the startup’s business-side operations to support the launch of a new cloud service, RisingWave Cloud, next year, CEO Yingjun Wu said.

Wu founded RisingWave in early 2021, after working on streaming processing and database systems for over a decade at companies including IBM and Amazon Web Services. While at AWS Redshift, Wu says he noticed that existing database systems like AWS Redshift, Snowflake and BigQuery couldn’t efficiently process of streaming data, while existing streaming systems were generally too complicated to most companies to use.

“I founded RisingWave Labs to make it easy to develop a cloud database system that can efficiently support stream processing,” Wu told ProWellTech in an email interview. “Building real-time applications leveraging streaming data should not incur operational overhead and become a barrier to entry. RisingWave aims to provide an easy on-ramp for sequel query language (SQL) users to begin their stream processing journey.”

Taking a step back for a moment, stream processing is the processing of data in motion — in other words, computing on data directly as it’s being produced or received. In the stream processing paradigm, app logic, analytics and queries exist continuously, and data flows through them continuously. Stream processing apps react to events from streams, for example triggering an action or updating a statistic. That’s as opposed to static, non-streaming setups where data is stored in a database and apps compute over it as needed, preventing the data from being processed concurrently.

Wu makes that case that only companies with deep pockets and data analytics expertise can adopt existing stream processing solutions, due to the complexity and high cost of ownership. Through RisingWave, he aims to change that with an open source streaming database that allows users to write code to continuously process data. The architecture separates the compute layer from storage, Wu claims, maximizing the efficiency of cloud resources.

Image Credits: RisingWave Labs

Wu notes that, among other use cases, RisingWave can support AI and machine learning applications, streaming data to AI systems to train and retrain them. It can also power real-time dashboards (e.g. traffic regions across a city), build services that provide aggregated information about a subject (such as the number of likes received on a tweet) and analyze and detect anomalies using SQL.

“Traditional database systems fail to offer the power of stream processing that allows users to make real-time decisions based on the most recent results,” Wu said. “Cost efficiencies built into our product using modern cloud-native architecture are very appealing for C-suite level managers. Besides the capital expenditures and operational expenditures aspects, the ease of use enhances developer productivity as RisingWave requires only the knowledge of SQL for any new users.”

RisingWave’s current focus is the aforementioned cloud service, RisingWave Cloud, a fully managed version of the company’s database engine. Currently in preview ahead of general availability next year, Wu says that “multiple” customers are actively piloting the service, with partners that include Confluent, StreamNative and Redpanda.

Wu concedes that there are competitors in the stream processing space, including Confluent’s KsqlDB, DeltaStream, Activeloop, Materialize, AWS Kinesis Data Analytics and several Apache Flink-based companies (see Immerok and Aiven). But he asserts neither they nor the broader slowdown in the tech industry will impact RisingWave’s go-to-market plans.

‘[We have] sufficient funding for the next two years,” Wu said. “In terms of tough economic headwinds, we do see an opportunity for new use cases to emerge, especially automated fraud detection in the financial services industry and others.”

Wu didn’t have revenue numbers to share when asked, but he said that he expects RisingWave’s headcount to expand from 40 today to about 48 by the end of the year, suggesting rather rosy internal growth projections.

In a statement via email, Yunqi Partners partner Yu Chen said: “We see that lowering the barrier to entry to deploy stream processing in both legacy as well as green field applications is critical to democratizing stream processing and unlocking the true potential of stream processing. There is no lack of tools to process data streams, but RisingWave is one of the very few designed as a database and can be easily plugged into a modern data stack to make real-time data intelligence a reality.”