# scylladb ScyllaDB is a high-performance distributed NoSQL database designed for scalability and low-latency data access. This is one page of public article previews, not the complete archive. Follow Next page to continue. Summaries are not the original full articles. ## A Self-Baked Async FFI Framework for Rust C# Interop DevFeed: [A Self-Baked Async FFI Framework for Rust C# Interop]() Original publisher: [Read original article]() Author: Cynthia Dunlop Published: 2026-08-31T13:00:34Z Content type: article Language: en Sources: [ScyllaDB]() Topics: [Rust](), [Tokio](), [.NET](), [C#](), [scylladb](), [For the Love of Code]() Tags: [c-sharp](), [drivers](), [engineering](), [hackathon](), [interop](), [rust](), [scylladb]() ### AI overview The article describes ScyllaDB's effort to build a Rust-based driver architecture with thin language-binding layers, focusing on a C# driver. It explains the motivation for creating a custom asynchronous FFI framework to connect Rust's Tokio runtime with .NET's async runtime over the C ABI, after existing binding-generation tools proved insufficient for Rust-C# async interoperation. ### Source excerpt How we got tokio and .NET's async runtime talking to each other, over the C ABI ## How Medium Powers Real-Time Recommendations at 1M OPS DevFeed: [How Medium Powers Real-Time Recommendations at 1M OPS]() Original publisher: [Read original article]() Author: Cynthia Dunlop Published: 2026-08-11T16:40:45Z Content type: article Language: en Sources: [ScyllaDB]() Topics: [real-time](), [scylladb](), [data](), [Machine learning](), [Inference](), [Software]() Tags: [architecture](), [data](), [inference](), [models](), [real-time](), [recommendation-system](), [scale](), [scylladb](), [user-stories]() ### AI overview The article explains how Medium's ScyllaDB-based feature store supports real-time recommendations. It describes processing user activity and new articles, storing features for recommendation models, and addressing data-modeling challenges as the system scaled to 1 million operations per second. ### Source excerpt Inside Medium's move from relational features to list features in its ScyllaDB-based feature store "Keep readers reading" is the not-so-simple goal of Medium's recommendations system. To predict what's most likely to appeal to a particular reader at any given time, Medium continuously processes user activity signals (stories read, recommendations shown, follows, likes, etc.). It then immediately correlates that with the steady stream of new articles, which is estimated at millions per month. Smart models and good inference logic are required, but that's not enough. The data must be stored and retrieved quickly enough to remain relevant while the user is [...] ## ScyllaDB Is Now Supported in MCP Toolbox for Databases DevFeed: [ScyllaDB Is Now Supported in MCP Toolbox for Databases]() Original publisher: [Read original article]() Author: Cynthia Dunlop Published: 2026-07-08T12:01:04Z Content type: article Language: en Sources: [ScyllaDB]() Topics: [scylladb](), [Model Context Protocol](), [MCP Server](), [AI Agent](), [Databases](), [Open Source]() Tags: [agents](), [ai-ml](), [databases](), [ecosystem](), [how-to](), [integration](), [mcp](), [mcp-server](), [open-source](), [scylladb](), [sdks](), [uncategorized]() ### AI overview This article explains the ScyllaDB integration added in version 1.5.0 of MCP Toolbox for Databases. It describes how the open-source MCP server connects AI agents and applications to self-hosted ScyllaDB clusters and ScyllaDB Cloud, and outlines installation, configuration, and CQL tool setup. ### Source excerpt Connect your AI agents to ScyllaDB using the new ScyllaDB integration in MCP Toolbox for Databases ## How Discord Automates ScyllaDB Clusters at Scale DevFeed: [How Discord Automates ScyllaDB Clusters at Scale]() Original publisher: [Read original article]() Author: Byte-Sized Design Published: 2026-06-15T06:30:00Z Content type: article Language: en Sources: [Byte-Sized Design]() Topics: [Discord](), [scylladb](), [Framework](), [Database]() Tags: [database](), [discord](), [framework](), [scale](), [scylladb]() ### AI overview An article about how Discord automates ScyllaDB cluster operations at scale, describing a framework that reduced a 36-hour database operation to two hours of mostly waiting. ### Source excerpt The framework that turned a 36-hour database operation into two hours of mostly waiting ## How Discord Processes 30+ Petabytes of Data DevFeed: [How Discord Processes 30+ Petabytes of Data]() Original publisher: [Read original article]() Author: Richard Oliver Bray Published: 2024-09-25T13:02:10Z Content type: article Language: en Sources: [Hacking Scale by Better Stack]() Topics: [Discord](), [data](), [scylladb](), [NoSQL](), [C++](), [Machine learning]() Tags: [c-plus-plus](), [data](), [discord](), [nosql](), [scylladb]() ### AI overview This article explains how Discord analyzes billions of daily messages and manages large-scale data processing. It describes message storage in ScyllaDB, data cleaning, machine-learning use cases, and Discord's development of Derived to automate data transformation for analysis. ### Source excerpt Discord's genius approach to automating insights from billions of messages