Lakehouse Architecture
A lakehouse is a data architecture that combines the cheap, open storage of a data lake with the performance, structure, and reliability of a data warehouse. It lets you run fast analytics directly on open files in object storage.
Combining the lake and the warehouse
Historically you chose between two worlds. Data warehouses gave you speed and structure but were proprietary and expensive and locked your data in. Data lakes gave you cheap, open, flexible storage but were slow and hard to govern. The lakehouse aims to get the best of both.
The key enablers are open table and file formats like Parquet, plus query engines fast enough to treat those open files like a warehouse. Your data stays open and cheap on object storage, but you get warehouse-grade query performance and structure on top of it.
It has become the dominant direction for modern analytical data platforms.
How Arc handles Lakehouse Architecture
Arc is aligned with the lakehouse model for time-series and analytical data. It stores open Parquet on object storage you own and provides a fast query engine on top, so you get warehouse-grade speed without giving up open, portable, low-cost storage.
Arc is a high-performance columnar database. Open Parquet on storage you own, single Go binary, production-ready in 30 seconds.