GlassFlow

Want an-all #opensource stack? No problem. @glassflowdev v2.4 is here with pipeline editing, kerberos-secured #Kafka clusters, and significantly optimized ingestion performance: github.com/glassflow Pair with #Coroot for out-of-the-box, zero-blindspot observability. Now with multi-cluster support: rb.gy/nolrfk The future is #FOSS 🐧💚 🪲🐝 #kubernetes #monitoring #observability #sysadmin #Linux #eBPF #softwarelibre #k8 #baremetal #VM #AI #tech #glassflow

Still duct-taping your #Kafka to ClickHouse® pipeline? No more fragile consumers or bloated frameworks. 🧰 @glassflowdev: Python-native, serverless stream processing 🚀 #AltinityCloud: Managed service for #ClickHouse that just works 📘 Full demo + code: hubs.la/Q03p439p0

Share your love with the @glassflowdev team with a Github star ⭐ ↓↓↓ github.com/glassflow/clic…

🐧☀️🚨#Opensource Spotlight: t.ly/18BGy Check out the exciting launch of @glassflowdev's #FOSS repo to improve your data streaming with deduplication and temporal join features for #Kafka and @ClickHouseDB. (Have a #freesoftware project you think could help our community next? send us a DM!)

🚨 Duplicates in your #Bitcoin → #ClickHouse pipeline? They hurt: 🔁 Block & TX duplicates 🐢 Slow queries 💸 FINAL is expensive Tried @glassflowdev — dedupes upstream, clean & fast. No ReplacingMergeTree hacks. No FINAL. Just relief.

A wonderful new open source project😄😄👍dev.to/esproc_spl/how…

Drowning in duplicate Kafka data or struggling with slow joins in ClickHouse? Meet GlassFlow — an open-source stream processor that makes real-time, clean data pipelines a breeze. 🧼⚡ No subscriptions. No bloat. Just results. 👇 Let me show you the magic: #Kafka #ClickHouse #ETL

@abhinavr8 @thegeeknarrator AFAIK, Trench is an event analytics storage and query engine that uses Kafka and ClickHouse as its underlying tech. But I haven't tried their product, to be honest. GlassFlow is a tool built for Kafka users to dedupe and join data before ingesting it to ClickHouse.

@thegeeknarrator @glassflowdev are they any different from trench.dev ?

DUPLICATE events and painfully SLOW joins are a real and painful problems in the world of stream processing and realtime analytics. But why there hasn't been a simple, easy and fast solution for these problems that just works with the hassle? Well, there is now. @glassflowdev is exactly doing that in an elegant manner. Just dropped a video on explaining why GlassFlow is super cool and why existing solutions have limitations. Checkout the link below for the video and also checkout the Github link and try out GlassFlow locally. youtu.be/Pr-OGNSFEqQ

Deduplicate and join streams from Kafta and ingest them into Clickhouse? A new open-source solution that makes this super easy by @glassflowdev. 🌐 ishortn.ink/EHFk61PI7Simon…

🥁 We just closed our seed round 🥳 Today is a big day. We just announced our $4.8m seed round led by brilliant minds from @upfrontvc . Learn at our blog post why every Python dev should be able to create event-driven data pipelines in minutes. glassflow.dev/blog/news-anno…

We have recently hosted a LinkedIn Live Webinar with GlassFlow.dev, Ulugbek Ergashev from datatruck, and Rodrigo Mansueli, M.Sc. from Supabase focusing on the emerging topic #GenAI with humans in loops feedback automation and their application in personalized recommendation solutions.

Want to keep your listings top-notch and search-friendly? Learn how to setup a real time Generative Feedback Loop (GFL) using @glassflowdev, @supabase, and Weaviate that brings AI-driven enhancements to Airbnb listings — ensuring data is always up-to-date and optimized for better search and personalized recommendations! Ready to start building? Check out this blog by @BoburUmurzokov: blog.glassflow.dev/real-time-gene…

@clcoding Very useful guide! Thanks for sharing! Some of the approaches we also use in our product to make it easy to build real-time data pipelines in Python. Check out: glassflow.dev

Free PDF Kindle Python For Data Science: Hands-On Guide To Learn Python Programming For Data Analysis And Visualization amzn.to/47hhAXA

@weaviate_io @wandb @cohere Quite an interesting and insightful course. Let us know if our team can collaborate in bringing more learning content for future courses.

We’re excited to announce the free RAG in Production course in collaboration with @wandb and @cohere 🧠 Learn about data ingestion and preprocessing, query enhancement, retrieval and re-ranking, and more! You can register for the pre-order here: wandb.courses/courses/rag-in…

@Redisinc We also used Redis as a vector database for AI our use cases. You can read more on our blog: blog.glassflow.dev/how-to-enrich-…

Redis is an essential part of the stack for AI. Redis for AI offers a vector database for faster retrieval-augmented generation (RAG) apps, making for quicker, faster responses. With semantic caching, your apps can answer frequently-asked questions 15X faster while reducing costly LLM calls by over 30%. Start building your AI with Redis for blazing fast performance and lower costs: redis.io/release

@supabase Thanks for sharing! Supabase is truly powerful. As part of our product, we are preparing several use cases for building real-time data pipelines with Supabase. Here is one of them blog.glassflow.dev/real-time-gene…

Supabase is now GA.

We’re thrilled to announce that we’ve extended our speaker lineup for our upcoming LinkedIn webinar! 🌟 Joining us is a special guest Rodrigo Mansueli from @supabase, who will showcase how Supabase handles real-time data with ease. linkedin.com/events/howtoim…

LinkedIn live webinar 🎬 : How to improve real-time AI response with GlassFlow.dev, @supabase , and @weaviate_io 𝐉𝐨𝐢𝐧 𝐭𝐨𝐩 𝐞𝐱𝐩𝐞𝐫𝐭𝐬 𝐢𝐧 𝐭𝐡𝐞 𝐝𝐚𝐭𝐚 𝐬𝐭𝐫𝐞𝐚𝐦𝐢𝐧𝐠 𝐚𝐧𝐝 𝐀𝐈 𝐟𝐢𝐞𝐥𝐝! linkedin.com/events/howtoim… #webinar #free

Below you see five popular stream processing patterns #streamprocessing #realtime