RisingWave Labs Raises $36M for Stream Processing Database
RisingWave Labs said it plans to expand its open-source stream processing database with $36 million in new funding as the vendor seeks to expand its technology and go-to-market efforts.
The San Francisco-based startup was founded in January 2021 with the goal of creating database technology designed specifically to manage streaming data from sources such as Apache Kafka.
RisingWave’s database aims to take streaming data and make it useful in real time for data analysis and business operations. The main database platform is written in the Rust open-source programming languagewhich offers improved security and performance.
With the funding, made public on October 18, the provider plans to build a cloud database as a service (DBaaS) which will be a managed version of the RisingWave open-source database.
The stream database technology market is occupied by several active vendors including Confluent, Redpanda, Hazelcast, and StreamNative.
In the not-too-distant future, data in motion — what streaming data provides — will be the norm, rather than data at rest, said David Menninger, analyst at Ventana Research.
David MenningerAnalyst, Ventana Research
RisingWave provides a way to use standard SQL queries to gain insights from real-time streaming data. There’s such a community of SQL-based skills and technologies that it’s no surprise to see SQL applied to streaming data, Menninger said.
“Extending standard SQL-based databases to process streaming data will make this process easier, making it easier for organizations to adopt streaming capabilities,” he said. “By using PostgreSQL-compatible SQL, RisingWave Labs has immediate access to a large ecosystem of compatible technologies and people who will know how to work with their product.”
Putting Stream Processing to Work in the RisingWave Database
Prior to founding RisingWave Labs, the company’s founder and CEO, Yingjun Wu, worked for several years as a researcher at the IBM Almaden Research Center, helping develop components for the IBM Db2 database. He also spent two years at Amazon as a software engineer with a focus on the Amazon Redshift database.
Wu said his goal with RisingWave is to make it easier for developers to use streaming data. Applications for the RisingWave Flow Database include real-time alerting and monitoring that can be used to power recommendation systems, security and operational dashboards.
Simply ingest streaming data from an event data streaming source like Apache Kafka is not sufficient to enable real-time information for alerts, analytics, or business operationssays Wu. Companies also need to create what’s called a materialized view, where RisingWave continuously processes data and makes it useful and available for SQL data queries.
RisingWave can also enable event-driven workflows, so as soon as data is ingested by the database, it can then trigger another process. For example, updating an entry on a corporate dashboard indicating the availability of a product or service.
How Rust Speeds Up the RisingWave Streaming Database
When Wu and his team first created the RisingWave database, it was originally developed in the C++ programming language. Seven months after writing the initial code in 2021, they rewrote the entire code base in Rust.
With C++, developers have to think about memory allocation and other complex techniques to enable security. By moving to Rust, the database gained memory-safe capabilities in the open-source programming language in which the compiler handles much of the complexity.
“We care a lot about memory safety because for a database system, we don’t really want to suffer from database crashes,” Wu said.
A private preview of the RisingWave DBaaS is available now, and the vendor plans to have a beta in Q1 2023.