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RisingWave Labs said it plans to grow its open source stream processing database with $36 million in new funding as the vendor looks to develop its technology and go-to-market efforts.
The San Francisco-based startup was founded in January 2021 with a goal of building a database technology designed specifically to handle 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 analytics and business operations. The core database platform is written in the open source Rust programming language, which provides enhanced security and performance.
The market for stream database technologies is busy with multiple 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, an analyst at Ventana Research.
David MenningerAnalyst, Ventana Research
RisingWave provides a way to use standard SQL queries to get insights from streaming data in real time There is such a large community of skills and technologies based on SQL that it's no surprise to see SQL applied to streaming data, Menninger said.
"Extending standard SQL-based databases to process streaming data will help with that process, 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 that will know how to work with their product."
Putting stream processing to work in the RisingWave database
Before starting RisingWave Labs, the company's founder and CEO, Yingjun Wu, worked for several years as a researcher at the IBM Almaden Research center helping to 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 enable developers to more easily use streaming data. Applications for the RisingWave stream database include real-time alerting and monitoring that can be used to power recommendation systems, security and operational dashboards.
Simply ingesting streaming data from an event data streaming source like Apache Kafka isn't enough to enable real-time insights for alerting, analytics or business operations, Wu said. Enterprises also need to create what is known as a materialized view, in which RisingWave processes the streaming data and makes it useful and available for SQL data queries.
RisingWave can also enable event-driven workflows, so that as soon as data is ingested by the database it can then trigger another process. For example, updating an entry on a business dashboard showing availability of a product or service.
How Rust accelerates the RisingWave streaming database
When Wu and his team first built the RisingWave database, it was initially developed in the C++ programming language. Seven months after they wrote the initial code in 2021, they rewrote the entire codebase in Rust.
With C++, developers need to think about memory allocation and other complex techniques in order to enable security. By moving to Rust, the database got memory safety capabilities in the open source programming language in which the compiler handles a lot of the complexity.
"We care a lot about memory safety because for a database system, we don't really want to suffer from any database crashes," Wu said.
A private preview of the RisingWave DBaaS is available now, and the vendor plans to have a beta version in the first quarter of 2023.