Author here, we’re just getting started with these experiments and plan to apply them to more features on our roadmap. Future posts will be more detailed, based on the feedback we received here. Once we finish implementing these features, we’ll be happy to share the code and dataset.
HN user
Debanitrkl
Founding Engineer @Parseable: Fast Observabiliy on S3
Author here, apologies for not making it clear on the post regarding the definition of Zero-shot time-series forecasting, but it's quite widely used and here's the definition of it "Zero-shot time-series forecasting is a framework for time-series prediction that does not require fine-tuning with specific time-series data to be predicted."
Good analysis and benchmarking, does using zero shot forecasting helps with less hallucinations?
Me: "I’m done trying every new database on HN." Also me, 3 minutes later: git clone https://github.com/kronotop/kronotop Damn it. You had me at "ACID + RESP3."
OLAP databases weren’t built for observability; they’re slow, expensive, and inefficient for high-cardinality telemetry. At Parseable, we took a different approach. Here’s why storage matters and how ParseableDB outperforms in real-world observability workloads.
Now that ClickHouse is moving towards becoming an observability platform, what does the future look like for other products like HyperDX that are essentially ClickHouse wrappers? Are we looking at another controversial license change?