Emily Le

Technical writer @ Singularity Data

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

Software engineer @ Singularity Data

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 @ Singularity Data

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 @ Singularity Data

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

Yingjun Wu

CEO @ Singularity Data

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

Next-Generation Streaming Database in the Cloud

Why RisingWave?

Highlight of Blogs

Next-Generation
Streaming Database
in the Cloud