Sync GitHub issues to BigQuery with CloudQuery, generate Vertex AI embeddings via BigQuery remote models, and deliver fast, fully managed semantic search and Q&A with Gemini—no vector database to run.
Mariano Gappa •
Turn GitHub issues into instant insights: sync with CloudQuery, generate PgVector embeddings in PostgreSQL, and answer natural-language questions with a tiny OpenAI-powered script.
Mariano Gappa •
How we built a Go-based MCP server to make AI Assistants AI data-aware, bridging code and database, which ended up transforming the way we code.
Mariano Gappa, +1 •
Lessons we learned from building an MCP server to bridge LLMs with cloud infrastructure databases. What we learned about tool descriptions, naming, context limits, and quirks, and how we fixed them.
Mariano Gappa, +1 •
Learn how to set up CloudQuery syncs within Databricks, including data transformation and visualization of your cloud asset inventory.
Mariano Gappa •
How we solved memory explosion issues in ClickHouse when processing billions of rows of cloud configuration data using an Insert-Splitter with UUID-range bucketing technique.
Mariano Gappa, +1 •
After six months using ClickHouse as CloudQuery’s default backend, here’s what we learned about performance, JOIN limitations, sorting keys, materialized views, and why real-world benchmarking matters.
Herman Schaaf, +2 •
CloudQuery introduces the JSON Flattener Transformer Integration, a new transformer integration that enables you to flatten JSON source data into separate columns at your destination.
Mariano Gappa •
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