Bytewax

🚀 Level Up Your Data Processing with Bytewax v0.20! Bytewax v0.20 brings critical updates to improve your workflow. The newly added Dataflow Visualizer provides a graphical representation of your data pipelines, making them easier to navigate and optimize. 🐝 We've also restructured our core operators to boost data handling efficiency, ensuring smoother operations within your applications. Ready to upgrade your data streams? ➡️ https://lnkd.in/e-WQPyxk

𝐁𝐲𝐭𝐞𝐰𝐚𝐱 𝐚𝐭 𝐏𝐲𝐃𝐚𝐭𝐚 𝐍𝐘𝐂: 𝐍𝐨 𝐓𝐫𝐢𝐜𝐤𝐬, 𝐉𝐮𝐬𝐭 𝐑𝐮𝐬𝐭𝐲 𝐏𝐲𝐭𝐡𝐨𝐧 𝐓𝐫𝐞𝐚𝐭𝐬! Happy Halloween, everyone! 🎃 We're thrilled to announce that Bytewax will be at PyData NYC by NumFOCUS from November 7th to 8th, sharing what makes real-time data streaming in Python 𝐬𝐜𝐚𝐥𝐚𝐛𝐥𝐞, 𝐟𝐚𝐬𝐭, and 𝐞𝐟𝐟𝐢𝐜𝐢𝐞𝐧𝐭! Our own Zander Matheson will explore the “spooky” secrets behind Bytewax’s core technology. His talk will explain 𝘸𝘩𝘺 𝘙𝘶𝘴𝘵 𝘱𝘰𝘸𝘦𝘳𝘴 𝘰𝘶𝘳 𝘦𝘯𝘨𝘪𝘯𝘦, 𝘦𝘹𝘱𝘭𝘰𝘳𝘪𝘯𝘨 𝘗𝘺𝘖3 𝘢𝘯𝘥 𝘩𝘰𝘸 𝘙𝘶𝘴𝘵 𝘮𝘢𝘬𝘦𝘴 𝘗𝘺𝘵𝘩𝘰𝘯 𝘧𝘢𝘴𝘵𝘦𝘳 (no black magic needed!). Curious about how to “oxidize” your Python code? Be there to find out! Swing by our booth to grab some Bytewax 🐝 swag and chat with our team about Python, Rust, and all things streaming tech. We can't wait to see you there! P.S. We've got another video gem from Zander Matheson! A must-watch—but maybe not for the easily moved. 😁 Enjoy!

𝐊𝐞𝐞𝐩𝐢𝐧𝐠 𝐀𝐈 𝐦𝐨𝐝𝐞𝐥𝐬 𝐮𝐩𝐝𝐚𝐭𝐞𝐝 𝐰𝐢𝐭𝐡 𝐭𝐡𝐞 𝐥𝐚𝐭𝐞𝐬𝐭 𝐝𝐚𝐭𝐚 𝐢𝐬 𝐚 𝐜𝐡𝐚𝐥𝐥𝐞𝐧𝐠𝐞 𝐰𝐞'𝐫𝐞 𝐚𝐝𝐝𝐫𝐞𝐬𝐬𝐢𝐧𝐠 𝐭𝐡𝐫𝐨𝐮𝐠𝐡 𝐫𝐞𝐚𝐥-𝐭𝐢𝐦𝐞 𝐩𝐫𝐨𝐜𝐞𝐬𝐬𝐢𝐧𝐠. 📊 By integrating Bytewax into RAG systems, we can process and incorporate new information as it arrives, ensuring our AI models generate responses that reflect the most current data. From a recent discussion: '𝘜𝘴𝘪𝘯𝘨 𝘰𝘱𝘦𝘯-𝘴𝘰𝘶𝘳𝘤𝘦 𝘵𝘰𝘰𝘭𝘴 𝘢𝘭𝘰𝘯𝘨 𝘸𝘪𝘵𝘩 𝘉𝘺𝘵𝘦𝘸𝘢𝘹, 𝘸𝘦 𝘤𝘢𝘯 𝘥𝘦𝘷𝘦𝘭𝘰𝘱 𝘴𝘤𝘢𝘭𝘢𝘣𝘭𝘦 𝘙𝘈𝘎 𝘴𝘺𝘴𝘵𝘦𝘮𝘴 𝘵𝘩𝘢𝘵 𝘱𝘳𝘰𝘷𝘪𝘥𝘦 𝘶𝘱-𝘵𝘰-𝘥𝘢𝘵𝘦 𝘪𝘯𝘧𝘰𝘳𝘮𝘢𝘵𝘪𝘰𝘯.' We're interested in how others are maintaining data freshness in AI models. Have you tried real-time data integration in your projects? Let's open a dialogue in the comments on the importance of real-time data in AI innovation. 🌐

[Tutorial] Learn how Bytewax seamlessly integrates with InfluxDB to tackle a common challenge: downsampling. 📉 🔽 By the end of this blog, you'll have a clear understanding of how to leverage Bytewax to build scalable data pipelines. https://bit.ly/40fhrCi #InfluxDB

Thrilled to announce that I’ll be speaking at #PyDataNYC by NumFOCUS Is Python always slow? Not if it's a bit Rusty! In my talk, I'll share how we built Bytewax with a Python interface and Rust core. We’ll cover PyO3, tips for integrating Rust, and how to keep Python’s flexibility while gaining efficiency. If you're curious about Rust in general, or especially if you want to level up your Python experience using Rust, don’t miss it! Join me on November 7 — register now!   https://lnkd.in/gJKJC_Xc I am also excited to share that we (Bytewax) are sponsoring #PyDataNYC this year, and our team will have a booth at the event. Come visit us for some cool swag and a special treat — perfect for exchanging ideas or simply having a good chat! We'd love to meet you there.

The new bytewax-redis module allows you to seamlessly integrate Redis streams and key-value stores into your Bytewax dataflows. Whether you're consuming data from Redis streams, writing processed data back to them, or interacting with Redis' key-value storage, bytewax-redis has you covered. cc: Zander Matheson

Exciting times at Bytewax! Here’s a quick look at what we’ve been working on recently: 🚀 bytewax-redis: We’ve integrated Redis’s in-memory storage with Bytewax for low-latency, real-time AI processing. ⚡ Bytewax x Estuary Flow’s Dekaf: We’ve made it easier to stream real-time data from databases like MongoDB into Bytewax with sub-100ms latency—no Kafka needed. 📊 Bytewax InfluxData Connector: Time-series data processing is now smoother and faster, making it perfect for predictive analytics and anomaly detection. 🔍 Real-Time RAG with Microsoft Azure AI Search: We’ve teamed up with Microsoft’s Co-Innovation Lab to create a Bytewax sink for Azure AI Search, helping you implement real-time NLP solutions. 📈 Bytewax ClickHouse Sink: The new ClickHouse Sink is here, offering seamless data transfer for real-time analytics workflows. 🧩 Bytewax Modules: We’ve rolled out advanced operators for complex data transformations, and more modules, including end-to-end dataflow, are coming soon. (all the links in the comments) We’re constantly working to simplify real-time data processing and integrate the tools that make it faster and easier for you to get insights. Stay tuned—there’s more to come!

🤔 𝐄𝐯𝐞𝐫 𝐰𝐨𝐧𝐝𝐞𝐫 𝐡𝐨𝐰 𝐫𝐞𝐚𝐥-𝐭𝐢𝐦𝐞 𝐬𝐭𝐫𝐞𝐚𝐦𝐢𝐧𝐠 𝐬𝐲𝐬𝐭𝐞𝐦𝐬 𝐝𝐞𝐭𝐞𝐜𝐭 𝐜𝐡𝐚𝐧𝐠𝐞𝐬 𝐰𝐢𝐭𝐡𝐨𝐮𝐭 𝐦𝐢𝐬𝐬𝐢𝐧𝐠 𝐚 𝐛𝐞𝐚𝐭? In our latest blog, we explored this question and walked through the technical process of building real-time update detection using Bytewax and Kafka. Learn how to set up reliable pipelines that detect updates on the fly using Alpaca news data, ensuring your system always runs on fresh information. ⚡ 𝘐𝘧 𝘺𝘰𝘶’𝘳𝘦 𝘸𝘰𝘳𝘬𝘪𝘯𝘨 𝘸𝘪𝘵𝘩 𝘳𝘦𝘢𝘭-𝘵𝘪𝘮𝘦 𝘥𝘢𝘵𝘢, 𝘮𝘪𝘴𝘴𝘪𝘯𝘨 𝘶𝘱𝘥𝘢𝘵𝘦𝘴 𝘪𝘴𝘯’𝘵 𝘢𝘯 𝘰𝘱𝘵𝘪𝘰𝘯. Read the full blog here to learn how to stay ahead! https://lnkd.in/dmyyYqGT

Last week, our own Zander Matheson tackled a burning question in the world of data processing: 𝐀𝐫𝐞 𝐊𝐚𝐟𝐤𝐚 𝐥𝐢𝐛𝐫𝐚𝐫𝐢𝐞𝐬 𝐟𝐨𝐫 𝐏𝐲𝐭𝐡𝐨𝐧 𝐚𝐥𝐰𝐚𝐲𝐬 𝐭𝐡𝐞 𝐛𝐞𝐬𝐭 𝐬𝐨𝐥𝐮𝐭𝐢𝐨𝐧? 🚀 The webinar focused on why pure Python alternatives are becoming a strong competitor. With over 500 registrations, it was clear that this topic is heating up! If you can't join us live, here is a recording. 🎥  https://lnkd.in/dD3HkDGp 💛 Special shout-out to Bobur U. for making it all happen! 

🚀 Catch the action at the Druid Summit by Imply tomorrow! 🚀 We're excited to see you in San Francisco for the panel "Real-Time Streaming Analytics," which will feature our own Zander Matheson, Julien Calfayan of Atlassian, Jeremy Ber of Amazon Web Services (AWS), Fred P. of Nstream, and Eric Sammer of Decodable, hosted by Rachel Pedreschi of claritype. Explore the dynamic world of real-time data analytics and discuss Apache Druid's integration with top streaming technologies. 😎 Secure your spot now and join us on October 22nd! https://lnkd.in/euPVA65c #ApacheFlink, #ApacheKafka, #Python.