Tinybird

Happy Independence Day from Tinybird to all our American friends! 🇺🇸 We made you a pie to celebrate. 🥧

Live demo on how to build analytics over DynamoDB tables with Tinybird, beginning to end. If you work with Amazon DynamoDB or are looking to migrate from Rockset (acquired by OpenAI) after their acquisition, this should interest you. Alasdair Brown will show how to capture DynamoDB change streams (CDC) in Tinybird, how to backfill or replace data with a snapshot, manage upserts, schema changes and more. And of course, how to build something on top of that data :-)

Looking to ingest DynamoDB data to Tinybird? Read our new guide. It walks you through using DynamoDB S3 Exports and DynamoDB Streams to capture historical and change data from DynamoDB and a custom Lambda function to send data to Tinybird's Events API. https://lnkd.in/d3EDqYVi

Are you going to be at AWS Summit in New York? Drop by booth 843 and talk to the Tinybird flock. We're stoked to meet with you! #AWSSummitNewYork

Next week, we're hosting a live workshop on how to capture DynamoDB change streams into Tinybird. You can register for that workshop here: https://bit.ly/45MqxYf Some context on how that's done: We can use DynamoDB S3 Exports and DynamoDB Streams to capture both historical and change data from DynamoDB and forward it to Tinybird using S3 and Lambda. In this case, a custom Lambda function forwards historical snapshots and change events to Tinybird via the Tinybird's Events API, an HTTP endpoint that easily handles ingestion and write operations to a Tinybird Data Source table. Join the workshop to see how it's done in real-time: https://bit.ly/45MqxYf #DynamoDB #changedatacapture #realtimeanalytics

At Tinybird, we move fast. "Speed Wins," as we like to say. But we always move as a flock. Together, with purpose. Interested in joining our team? Here's a list of our open roles: 🇪🇺🧰 ClickHouse Site Reliability Engineer https://bit.ly/3zsoD2K 🇪🇺🧰 Site Reliability Engineer https://bit.ly/4cNt8Dh 🇪🇺🧰 ClickHouse Developer https://bit.ly/4cmUosH 🇪🇺🧰 Product Front-End Engineer https://bit.ly/3xHosQz 🇪🇺💰 Sales Development Representative https://bit.ly/3L9TOT0 🇪🇸💰 Sales Development Representative (Spain) https://bit.ly/4cOvrGt 🇪🇺🏖️ Marketing Coordinator https://bit.ly/4cIrO4P 🇺🇸🏖️ Senior Product Marketing Manager https://bit.ly/4cLj8uA Check out all our open roles at https://bit.ly/3zpZxBz

A few weeks ago, we shipped Tinybird Charts, the fast, easy way to create custom visualizations of your real-time data. Today, we're excited to ship a chart type many of you have requested: Tables! Take any Tinybird API Endpoint, create a tabular chart of the data, copy the code, and add it to your website or dashboard. Easy! Learn more about Tinybird Charts 👉 https://lnkd.in/d42SjnzH

What is the difference between a user-facing dashboard and a regular dashboard? It's the difference between user-facing real-time analytics and business intelligence. User-facing analytics is quite different from Business Intelligence (BI). Business Intelligence utilizes batch processes to extract data from source systems, transform it to create data models, and load it into a data storage platform connected to BI tools used by a few internal stakeholders. With BI, you have complex queries with relatively high response latency serving only a handful of concurrent users. User-facing analytics, on the other hand, is meant to provide on-demand analytics views for external users. Data analytics are embedded into user-facing apps and refreshed as users interact with the data visualization components or data-driven features. With user-facing analytics, you still have complex queries, but data freshness is measured in seconds or less, query latency must shrink to milliseconds, and request concurrency can grow to thousands or millions of requests per second. Read more in our definitive guide to user-facing analytics 👉 https://bit.ly/3wNeM6I

Are you a former Rockset customer looking to find a new home for your real-time scenarios? We're running a workshop on how to ingest data from Amazon DynamoDB. In this session, you will: - Capture changes from DynamoDB with Kafka Connect - Stream changes to Tinybird (using Kafka) - Finalize the change stream in Tinybird - Build analytics and publish REST APIs Tinybird is the real-time platform that enables you to unify your batch and streaming data, write queries in SQL, and publish queries as fast REST APIs. Build real-time user-facing analytics quickly. Register today! https://lnkd.in/ddsFD4ir

Leaderboards aren't just for games. Be sure to check out our blog post on Building Real-Time Leaderboards with Tinybird. https://bit.ly/3Xmggzz