Lakehouse & Table Formats
A curated collection of the best table formats and lakehouse storage layers for scraped datasets. Querying and compute are provided by compatible engines.
Quick answer
Write scraped datasets as managed tables over stored files, then query them with a compatible engine. Apache Iceberg is an open table format, Delta Lake provides lakehouse table features, and Apache Hudi supports incremental ingestion and upserts. These are table and storage layers, not complete standalone query databases; check compatibility with your compute and catalog stack.
Frequently asked questions
What is a data lakehouse?
A data lakehouse combines flexible data lake storage with table management and warehouse-style query workloads. For example, Databricks uses Delta Lake for table transactions and schema handling, with separate governance capabilities. Object storage alone does not provide all of these layers.
Sources (checked ): Databricks lakehouse overview; Delta Lake introduction
Is Amazon S3 a data lake?
Amazon S3 is object storage that can hold the files in a data lake. A usable data lake also needs choices about ingestion, organization, access and querying. A lakehouse adds table management capabilities, such as Delta Lake transactions; an S3 bucket alone does not establish that architecture.
Sources (checked ): Amazon S3 overview; Delta Lake introduction