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You can discover which Mastodon tooters also tweeted using my favorite kind of Steampipe query.
The compactor handles critical post-ingestion and pre-query workloads in the background on a separate server, enabling low latency for data ingestion and high performance for queries.
Elasticsearch, which is an Apache’s Lucene library-based search engine, can be used to run full-text search queries on JSON documents via a web interface.
When viewing the people you follow on Mastodon, it’s helpful to know which lists (if any) you’ve assigned them to. Here's how you can do that with SQL and Steampipe.
Seattle-based Kaskada claims to be the first company to train machines using event-based data and real-time data being fed from streaming sources.
Updates and deletes remove history that is often desirable to keep. It is not only possible but practical to write a database application that preserves that history.
A dashboard+feed reader built with SQL gives you an easy and natural way to consume as much, or as little, Mastodon activity as you like.
Getting your data to tell you what you don’t know requires analytics. And analytics requires cloud.
Our brains are built to take in a lot of information at a glance, and if it’s organized well we can do that very effectively. Applying filters helps.
Steampipe’s SQLification of the Mastodon API is a handy way to track activity in the fediverse. Use it to do Mastodon analytics, find interesting people, and more.