# Engineering Excellence Published articles for Engineering Excellence. This is one page of public article previews, not the complete archive. Follow Next page to continue. Summaries are not the original full articles. ## From OLTP to OLAP: 7 ClickHouse® Optimization Mistakes DevFeed: [From OLTP to OLAP: 7 ClickHouse® Optimization Mistakes]() Original publisher: [Read original article]() Author: Iago Enríquez Published: 2026-08-03T10:00:00Z Content type: article Language: en Sources: [Tinybird]() Topics: [clickhouse](), [Optimization]() Tags: [clickhouse](), [engineering-excellence](), [mistakes](), [olap](), [optimization]() ### AI overview A practical article about seven ClickHouse optimization mistakes encountered when moving from OLTP to OLAP workloads. ### Source excerpt Practical lessons from optimizing analytical workloads in ClickHouse®. ## Tracking Down Orphaned Objects in ClickHouse Clusters and Improving Cleanup and Recovery DevFeed: [Tracking Down Orphaned Objects in ClickHouse Clusters and Improving Cleanup and Recovery]() Original publisher: [Read original article]() Author: Irene Martínez Published: 2026-05-19T00:00:00Z Content type: article Language: en Sources: [Tinybird]() Topics: [clickhouse](), [data](), [incident](), [cloud-infrastructure]() Tags: [cleanup](), [clickhouse](), [clusters](), [data](), [engineering-excellence](), [incident](), [recovery](), [storage]() ### AI overview This article describes how the team tracked down orphaned objects in its ClickHouse clusters, reduced monthly storage costs, and improved cleanup and recovery procedures after a near data-loss incident. ### Source excerpt How we tracked down petabytes of orphaned objects in our ClickHouse clusters, recovered tens of thousands of dollars in monthly storage costs, and hardened our cleanup and recovery procedures after almost losing data along the way. ## From 48 Seconds to 130 Milliseconds: Vector Search in Tinybird DevFeed: [From 48 Seconds to 130 Milliseconds: Vector Search in Tinybird]() Original publisher: [Read original article]() Author: Daniel Sangorrín Published: 2026-05-12T00:00:00Z Content type: article Language: en Sources: [Tinybird]() Topics: [Embeddings](), [AI search]() Tags: [customer](), [embeddings](), [engineering-excellence](), [search](), [vector](), [vector-search]() ### AI overview A customer needed semantic search over 20 million embeddings, but the initial attempt timed out. The article reports that three changes reduced query latency to under 200 milliseconds. ### Source excerpt A customer needed semantic search over 20 million embeddings. Their first attempt timed out. Three changes turned it into sub-200ms queries. Here's what we learned. ## Project Kijiji: building a GNN-based routing intelligence platform for fragile networks DevFeed: [Project Kijiji: building a GNN-based routing intelligence platform for fragile networks]() Original publisher: [Read original article]() Author: Elvis Muchiri Published: 2026-05-08T00:00:00Z Content type: article Language: en Sources: [Tinybird]() Topics: [Routing (disambiguation)](), [networking](), [Networks](), [Internet]() Tags: [building](), [engineering-excellence](), [internet](), [map](), [networks](), [peering](), [platform](), [routing]() ### AI overview This article describes Project Kijiji, a GNN-based platform that uses Tinybird to map inefficiencies in African internet routing and predict where new IXP peering agreements could have the greatest regional impact. ### Source excerpt How a GNN-based platform uses Tinybird to map African internet routing inefficiencies and predict where new IXP peering agreements would have the highest regional impact. ## Finding and fixing bugs in ClickHouse®'s Alias table engine DevFeed: [Finding and fixing bugs in ClickHouse®'s Alias table engine]() Original publisher: [Read original article]() Author: Enric Calabuig Published: 2026-04-13T00:00:00Z Content type: article Language: en Sources: [Tinybird]() Topics: [clickhouse](), [Testing]() Tags: [bugs](), [clickhouse](), [engineering-excellence](), [experimental](), [testing]() ### AI overview The article reports testing ClickHouse's experimental Alias table engine, identifies bugs in DDL dependency tracking and materialized-view triggering, and notes that a fix for the dependency-tracking bug was submitted upstream. ### Source excerpt We've been testing ClickHouse®'s experimental Alias table engine. We found bugs in how DDL dependencies are tracked and in how materialized views are triggered and shipped a fix upstream for the former. ## Smarter deployments in Tinybird: faster schema changes for the most common operations DevFeed: [Smarter deployments in Tinybird: faster schema changes for the most common operations]() Original publisher: [Read original article]() Author: Jordi Orihuela Published: 2026-03-25T00:00:00Z Content type: release Language: en Sources: [Tinybird]() Topics: [Structured-data]() Tags: [engineering-excellence](), [schema]() ### AI overview Tinybird deployments now support ALTER TABLE for simple schema changes, allowing those changes to deploy in seconds instead of requiring a full table rebuild. ### Source excerpt Most schema changes don't need a full table rebuild. We added ALTER TABLE support to Tinybird deployments so simple changes deploy in seconds, not minutes. ## How Tinybird's storage architecture works: S3, local caching, and zero-copy replication DevFeed: [How Tinybird's storage architecture works: S3, local caching, and zero-copy replication]() Original publisher: [Read original article]() Author: Daniel Pozo, Irene Martínez Published: 2026-03-02T10:00:00Z Content type: article Language: en Sources: [Tinybird]() Topics: [clickhouse](), [Amazon S3](), [Caching](), [Replication](), [cloud-infrastructure]() Tags: [architecture](), [caching](), [clickhouse](), [engineering-excellence](), [object-storage](), [replication](), [run](), [s3](), [ssd](), [storage](), [zero-copy]() ### AI overview This article explains how Tinybird runs ClickHouse on object storage using local SSD caching, zero-copy replication, and a packed part format. It states that the format reduces S3 costs by 30-40%. ### Source excerpt How we run ClickHouse on top of object storage with local SSD caching, zero-copy replication, and a packed part format that cuts S3 costs by 30-40%. ## How Tinybird Built Branches to Share Production Data Without Copying It DevFeed: [How Tinybird Built Branches to Share Production Data Without Copying It]() Original publisher: [Read original article]() Author: Alberto Romeu Published: 2026-02-26T00:00:00Z Content type: article Language: en Sources: [Tinybird]() Topics: [clickhouse](), [Kafka](), [Amazon S3](), [CI/CD]() Tags: [ci-cd](), [clickhouse](), [engineering-excellence](), [kafka](), [s3](), [zero-copy]() ### AI overview An engineering article about Tinybird branches, covering zero-copy production-data sharing through ClickHouse metadata, Kafka consumer group isolation, S3 sample imports, and CI/CD preview deployments. ### Source excerpt The engineering behind Tinybird branches: zero-copy partition sharing via ClickHouse metadata, Kafka consumer group isolation, S3 sample imports, and CI/CD preview deployments. ## How We Built Tinybird's TypeScript SDK for ClickHouse DevFeed: [How We Built Tinybird's TypeScript SDK for ClickHouse]() Original publisher: [Read original article]() Author: Rafa Moreno Published: 2026-02-19T00:00:00Z Content type: article Language: en Sources: [Tinybird]() Topics: [SDK](), [TypeScript](), [clickhouse](), [Development](), [data]() Tags: [clickhouse](), [data](), [dev](), [engineering-excellence](), [sdk](), [typescript]() ### AI overview An article explains how Tinybird built its TypeScript SDK for ClickHouse, covering phantom types for compile-time inference, esbuild for schema loading, and a development workflow connecting the application and data layer. ### Source excerpt How we built the Tinybird TypeScript SDK: phantom types for compile-time inference, esbuild for schema loading, and a dev workflow that connects your app and data layer. ## How We Built Time Series: Configuration-Driven Visualization in Tinybird Forward DevFeed: [How We Built Time Series: Configuration-Driven Visualization in Tinybird Forward]() Original publisher: [Read original article]() Author: Julia Vallina Published: 2026-02-09T00:00:00Z Content type: article Language: en Sources: [Tinybird]() Topics: [Time Series](), [clickhouse](), [SQL](), [configuration](), [debug]() Tags: [clickhouse](), [configuration](), [debug](), [engineering-excellence](), [sql](), [time-series](), [visualization]() ### AI overview An account of how Tinybird rebuilt its Time Series feature, focusing on the SQL problems encountered, the ClickHouse patterns used, and its use for debugging alerts. ### Source excerpt How we rebuilt Time Series: the SQL problems we hit, the ClickHouse patterns we used, and how we use it to debug our own alerts. ## How We Built Playgrounds: Bringing Browser-Based SQL Back to Tinybird Forward DevFeed: [How We Built Playgrounds: Bringing Browser-Based SQL Back to Tinybird Forward]() Original publisher: [Read original article]() Author: Rafa Moreno Published: 2026-02-04T00:00:00Z Content type: article Language: en Sources: [Tinybird]() Topics: [SQL](), [browser](), [Redis](), [Artificial Intelligence]() Tags: [ai](), [browser](), [engineering-excellence](), [redis](), [sql]() ### AI overview A technical deep-dive into the architecture of Tinybird Playgrounds, covering Redis storage, workspace sharing, split-screen panels, template parameters, and AI-assisted SQL with diff preview. ### Source excerpt A technical deep-dive into the architecture decisions behind Playgrounds: Redis storage, workspace sharing, split-screen panels, template parameters, and AI-assisted SQL with diff preview. ## How we built a production Kafka connector for ClickHouse® DevFeed: [How we built a production Kafka connector for ClickHouse®]() Original publisher: [Read original article]() Author: Alberto Romeu, Jordi Vilaseca Published: 2026-01-22T00:00:00Z Content type: article Language: en Sources: [Tinybird]() Topics: [clickhouse](), [Kafka]() Tags: [clickhouse](), [engineering-excellence](), [events](), [kafka](), [operational](), [production]() ### AI overview The article describes how the publisher built a production Kafka connector for ClickHouse, presenting it as scalable and reliable, capable of processing billions of events with minimal operational overhead. ### Source excerpt How we built a scalable, reliable Kafka connector that processes billions of events with minimal operational overhead ## Backpressure improvements help prevent data loss during ingestion traffic spikes DevFeed: [Backpressure improvements help prevent data loss during ingestion traffic spikes]() Original publisher: [Read original article]() Author: Javier Goizueta Published: 2025-11-18T12:00:00Z Content type: article Language: en Sources: [Tinybird]() Topics: [data]() Tags: [backpressure](), [data](), [engineering-excellence]() ### AI overview The article explains that backpressure improvements help prevent data loss during traffic spikes and keep ingestion reliable when volume exceeds expectations. ### Source excerpt Backpressure improvements prevent data loss during traffic spikes. Ingestion stays reliable even when volume exceeds expectations. ## How Software Engineering Teams Can Improve Performance and Engineering Excellence DevFeed: [How Software Engineering Teams Can Improve Performance and Engineering Excellence]() Original publisher: [Read original article]() Author: tobi@techunicorn.builders (Tobias Mende) Published: 2025-05-21T00:00:00Z Content type: opinion Language: en Sources: [Tobias Mende]() Topics: [Software Engineering](), [engineering-culture](), [Self-organizing Team](), [Agile]() Tags: [agile](), [engineering](), [engineering-excellence](), [performance](), [productivity](), [teams]() ### AI overview This talk examines why software engineering teams may plateau at average performance and presents practical habits, team activities, and mindset shifts intended to support higher performance, motivation, teamwork, and engineering excellence without micromanagement or pressure. ### Source excerpt Most software engineering teams operate far below their capabilities. They perform okay, good enough, or average. But what if any team can reach higher productivity, joy, and excellence? In this session, we will discover why most teams do not use their full potential and what every one of us can do to lead our teams toward high performance and engineering excellence. ## Building a conversational AI tool for real-time analytics DevFeed: [Building a conversational AI tool for real-time analytics]() Original publisher: [Read original article]() Author: Rafa Moreno Published: 2025-05-06T00:00:00Z Content type: tutorial Language: en Sources: [Tinybird]() Topics: [Conversational AI](), [real-time](), [data](), [Tool]() Tags: [ai](), [building](), [conversational-ai](), [data](), [engineering-excellence](), [real-time](), [tool]() ### AI overview Tinybird describes how it built a conversational AI feature that lets users chat with their data for real-time analytics. ### Source excerpt We just launched a conversational AI feature. Here's how we built the feature that lets you chat with your data. ## How to safely cancel a database query DevFeed: [How to safely cancel a database query]() Original publisher: [Read original article]() Author: Iván Malagón Published: 2025-04-07T00:00:00Z Content type: tutorial Language: en Sources: [Tinybird]() Topics: [Database]() Tags: [database](), [engineering-excellence](), [how-to]() ### AI overview This tutorial presents an approach for safely canceling database queries while avoiding data corruption, resource leaks, and problematic edge cases. ### Source excerpt How to safely cancel a database query without corrupting data or leaving resources hanging. This approach handles edge cases cleanly. ## How to break the cycle of firefighting and build engineering excellence DevFeed: [How to break the cycle of firefighting and build engineering excellence]() Original publisher: [Read original article]() Author: jesalg Published: 2025-01-01T00:00:00Z Content type: tutorial Language: en Sources: [Jesal Gadhia]() Topics: [Development](), [systems](), [reactive]() Tags: [career](), [development](), [engineering](), [engineering-excellence](), [how-to](), [leadership](), [patterns](), [prevent](), [reactive](), [software-development](), [systems]() ### AI overview This article explains how engineering leaders can break out of reactive firefighting by using systems thinking. It introduces the iceberg model, distinguishing visible events from recurring patterns and deeper causes, and argues that identifying persistent patterns can support more proactive engineering practices. ### Source excerpt Exercise better foresight by identifying patterns, pinpointing what makes them persist, and understanding what could prevent it in the future ## Why Tinybird Rebuilt Its Frontend Instead of Patching It DevFeed: [Why Tinybird Rebuilt Its Frontend Instead of Patching It]() Original publisher: [Read original article]() Author: Rafa Moreno, Alasdair Brown Published: 2024-07-19T00:00:00Z Content type: article Language: en Sources: [Tinybird]() Topics: [Front end](), [Code](), [User experience (UX)]() Tags: [code](), [engineering-excellence](), [frontend](), [refactor](), [ux]() ### AI overview Tinybird describes a complete frontend refactor, citing faster loads, better UX, and cleaner code as reasons for rebuilding instead of patching. ### Source excerpt We refactored the Tinybird frontend completely. Faster loads, better UX, cleaner code. Here's why we rebuilt instead of patched. ## Tinybird Announces Rebuilt Documentation with Improved Search, Examples, and Tutorials DevFeed: [Tinybird Announces Rebuilt Documentation with Improved Search, Examples, and Tutorials]() Original publisher: [Read original article]() Author: Julia Vallina Published: 2024-04-15T00:00:00Z Content type: release Language: en Sources: [Tinybird]() Topics: [Documentation]() Tags: [docs](), [engineering-excellence](), [examples](), [search](), [tutorials]() ### AI overview Tinybird rebuilt its documentation from scratch, adding improved search, clearer examples, and real-world tutorials to help readers find answers faster. ### Source excerpt New docs make finding answers faster. Rebuilt from scratch with better search, clearer examples, and real-world tutorials. ## Schema migrations for streaming ClickHouse tables across clusters DevFeed: [Schema migrations for streaming ClickHouse tables across clusters]() Original publisher: [Read original article]() Author: Alberto Romeu Published: 2024-03-11T00:00:00Z Content type: tutorial Language: en Sources: [Tinybird]() Topics: [clickhouse](), [Streaming](), [Structured-data]() Tags: [clickhouse](), [clusters](), [engineering-excellence](), [migrations](), [production](), [schema](), [streaming]() ### AI overview This article describes an approach for performing schema migrations on streaming ClickHouse tables across clusters. ### Source excerpt Schema migrations on a streaming ClickHouse table? At 100s of MB/s? Here's how we do it across clusters without losing a single bit. ## Resolving a year-long ClickHouse® lock contention DevFeed: [Resolving a year-long ClickHouse® lock contention]() Original publisher: [Read original article]() Author: Jordi Villar Published: 2023-10-30T00:00:00Z Content type: article Language: en Sources: [Tinybird]() Topics: [clickhouse]() Tags: [clickhouse](), [engineering-excellence](), [performance]() ### AI overview This article describes resolving a ClickHouse lock contention problem that had stumped the team for over a year, resulting in a reported 5x performance improvement. ### Source excerpt Here's how we fixed a problem that had stumped us for over a year and saw a 5x performance improvement in the process. ## Improving Developer Experience, Level 3: The Triad of Clarity, Focus, and Flow DevFeed: [Improving Developer Experience, Level 3: The Triad of Clarity, Focus, and Flow]() Original publisher: [Read original article]() Author: tobi@techunicorn.builders (Tobias Mende) Published: 2023-08-26T04:00:00Z Content type: opinion Language: en Sources: [Tobias Mende]() Topics: [devex](), [Developer experience](), [Development](), [iteration]() Tags: [developer-experience](), [developer-experience-developer-productivity-engineering-excellence](), [engineering-excellence](), [flow](), [focus](), [loops](), [sync]() ### AI overview This article examines clarity, focus, and flow as connected dimensions of developer experience. It discusses purpose-driven development, defined outcomes, iterative feedback, and autonomy as ways to improve engineering work. ### Source excerpt Improving Developer Experience, Level 3: The Triad of Clarity, Focus, and Flow Last week, we delved deep into "Belonging, Collaboration, and Communication". Further up in the Maslow Pyramid of DevEx, we have the factors that affect focus, clarity, and flow. This article will explore how we can improve those factors. ## A Python story about the GIL, threading, and replacing ProcessPoolExecutor DevFeed: [A Python story about the GIL, threading, and replacing ProcessPoolExecutor]() Original publisher: [Read original article]() Author: Tinybird Published: 2023-08-09T00:00:00Z Content type: opinion Language: en Sources: [Tinybird]() Topics: [Python](), [Code]() Tags: [code](), [engineering-excellence](), [python](), [threading]() ### AI overview A story about Python's GIL and threading, describing work to fix code that already works and replace ProcessPoolExecutor. ### Source excerpt A story about the Python GIL, threading, and fixing code that already works. ## Adding JOIN support for parallel replicas on ClickHouse® DevFeed: [Adding JOIN support for parallel replicas on ClickHouse®]() Original publisher: [Read original article]() Author: Javi Santana Published: 2023-06-08T00:00:00Z Content type: release Language: en Sources: [Tinybird]() Topics: [clickhouse]() Tags: [clickhouse](), [distributed](), [engineering-excellence](), [parallel]() ### AI overview Tinybird announces JOIN support for parallel replicas in ClickHouse, enabling distributed queries that were previously unsupported and are described as significantly faster. ### Source excerpt Parallel replicas in ClickHouse couldn't handle JOINs. We fixed that. Now your distributed queries just got significantly faster. [Next page]()