Our architecture is built around columnar design, and we use Apache Arrow for in-memory columnar processing and Apache Parquet for durable columnar storage on S3-compatible object storage. In Parseable, every labels stay as columns in the data instead of becoming a large long-lived per-series index like many TSDBs.
msandford•7m ago
100M active time series is good information, but what's the data rate for each time series it can handle? One update per minute or 10 per second? There's a factor of 600 difference there. Neither is obviously insanely the wrong update rate.
yashdotrv•20m ago
This is Yash, founding team at Parseable (https://github.com/parseablehq).
We've built an open source observability data lake using Rust, that handles high-cardinality data at around 100M active time series in production (https://www.parseable.com/blog/how-parseable-handles-100-mil...)
Our architecture is built around columnar design, and we use Apache Arrow for in-memory columnar processing and Apache Parquet for durable columnar storage on S3-compatible object storage. In Parseable, every labels stay as columns in the data instead of becoming a large long-lived per-series index like many TSDBs.
msandford•7m ago