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In the past, I also had doubts about whether a Rust database built on open-source components would be performance-limited, but this evaluation has dispelled our concerns. Apache DataFusion + Arrow + Parquet + OpenDAL, as a new data stack, have proven their potential.
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Big question I have is: should I invest in DeltaLake/Iceberg based solution, or something like this?
Delta Lake and Iceberg are great for managing offline, big data workloads like batch analytics and ETL on data lakes. They're not built for real-time queries or high-throughput writes.

GreptimeDB, on the other hand, is optimized for real-time, time-series data like IoT and observability metrics, but it's not suited for offline batch processing.

Choose Delta Lake or Iceberg for offline analytics at scale. Use GreptimeDB for fast, real-time data ingestion and queries. Together, they can complement each other: GreptimeDB handles real-time data, while Delta Lake/Iceberg manages offline analytics.

Thank you. I've previously tried Databend but it was very slow at multiple individual inserts. Will try GreptimeDB next time I have a chance!