Rayees Pasha

Head of Product @ RisingWave Labs

Somrita Ganchoudhuri

Marketing Communications Manager @ RisingWave Labs

We believe focusing on messaging is just as important as the focus on product differentiation. Keeping this in mind, we are changing our company name to RisingWave Labs. After all, RisingWave is at the heart of our innovation. And this change will allow us to stay close to our product and the RisingWave community.

We are RisingWave Labs now!

Shunjie Ding

Software Engineer @ RisingWave Labs

RisingWave is a cloud-native streaming database. It is designed to fully leverage the elasticity provided by the cloud. However, deploying and maintaining RisingWave on the cloud is still a challenging technical problem. To tackle the problem, we developed the RisingWave operator, an extension that features the operations of managing RisingWave on Kubernetes. It supports out-of-the-box restarting, scaling, and upgrading operations on a RisingWave cluster. The RisingWave operator is now open-sourced and it is one step further toward the cloud era for RisingWave.

One Step Towards Cloud: The RisingWave Operator

Yingjun Wu

CEO @ RisingWave Labs

Everyone is talking about the modern data stack (MDS) nowadays. I am a data system person. I started building core database systems in the big data era, and have witnessed the birth and prosperity of cloud computing over the last decade. But the first time I came across the term “modern data stack,” I felt confused - is it just yet another buzzword that the cloud service vendors created to attract people’s eyeballs? There are so many articles online, but most of them are quite markety and salesy. After running a startup building core systems in the modern data stack domain for a while, I would like to share my thoughts. In this article, I will explain “modern data stack” to you in simple terms, and discuss why modern data stack can really matter in companies.

Everything You Wanted to Know but were Afraid to Ask about Modern Data Stack (part I)

Emily Le

Technical Writer @ RisingWave Labs

As companies collect increasing amounts of data daily, it is crucial to query and analyze the data to make timely decisions quickly. To support such business scenarios, OLAP and stream processing are two popular techniques that promise to deliver analytical results with low latency. However, since both techniques claim to target real-time analysis, it can be quite confusing when trying to understand the differences between them and when to use them. What is OLAP? What is stream processing? How are they different from each other? This blog answers these questions by comprehensively comparing OLAP and stream processing.

Real-time analytics: how is OLAP different from stream processing?

Tao Wu

Heng Ma

Social media platforms like Twitter process a high volume of messages every second. To gain insights from social media platform data in real-time, companies need to adopt stream processing in their tech stack. However, this can be a struggle as many stream processing frameworks are complicated to design and implement. This blog presents how RisingWave can seamlessly work with Apache Pulsar to provide a real-time data streaming solution, making real-time applications much easier to build and maintain.

Tutorial: Pulsar + RisingWave for Fast Twitter Event Processing

Jovana

Community Manager @ RisingWave Labs

Open-source mascots have been widely considered synonyms for their projects/products. So, it should come as no surprise that we thought RisingWave too, deserves a mascot that will add an element of fun to the often-intimidating world of stream processing. Meet Wavy, a squid that won our hearts and will help us keep RisingWave a welcoming and friendly community.

Hello World, Meet Wavy

Chi Zhang

Software Engineer Intern @ RisingWave Labs

Building the development environment manually for RisingWave is painful. We have developed RiseDev, the developer tool, to drastically simplify the development process. It automates the process of starting and deploying a full RisingWave cluster and makes the development process much smoother and more efficient.

Developer Experience Counts: Behind the Scenes of RiseDev

The amount of streaming data has grown explosively over the past few years. A lot of businesses realize that they need to move to stream processing, but they have a hard time figuring out the route to take. 

Build and Maintain Real-time Applications Faster and Easier with Redpanda and RisingWave

Two months ago, we open-sourced RisingWave, a cloud-native streaming database. RisingWave is developed on the mission to democratize stream processing — to make stream processing simple, affordable, and accessible.

On the Way to Democratized Stream Processing: RisingWave’s Roadmap

As an early-stage database startup, we entirely deleted our C++ codebase after 7 months of development and rewrote everything from scratch in Rust programming language. Here's how we arrived at a decision and why we think this was one of the best decisions ever.

Building a Cloud Database from Scratch: Why We Moved from C++ to Rust

Two weeks ago, we open-sourced RisingWave, a cloud-native streaming database. And in no time, the project gained lots of attention from the open-source community and became the #1 trending project written in Rust!

Is RisingWave the Next Apache Flink?

Stream processing is a well-studied topic. Over the last few decades, researchers and practitioners have devoted substantial efforts to developing fast, scalable, and reliable streaming systems tailored for real-time analytics over streaming data.

Next-Generation
Streaming Database
in the Cloud

Why RisingWave?

Highlight of Blogs

Explore More

RisingWave Labs Meetup