Although this is still in preview as of this writing, they are working with external engines such as Trino to make sure there is full interoperability between them. Hence the reason for the creation of the Unity catalog and the migration of their customers to it over the coming years.ĭatabricks is migrating its existing customers to Unity and thankfully they have kept to their open source roots by exposing a Metastore API illustrated below. The problem with these repositories is that they are just used to store object metadata and not additional information such as access control and additional metadata. In the past, Databricks has supported external catalogs such as AWS Glue and Hive-compatible metastores. Metadata on objects are applied via “ tags ”. It’s a fully featured catalog that includes governance (role-based access control). Databricks (Delta Lake only)ĭatabricks created the Unity Catalog which only works with Delta Lake. Now, let’s talk data catalogs and how each vendor is supporting table format catalogs for Delta Lake and Iceberg. Now that we’ve quickly covered what Iceberg and Delta catalogs contain, (pretty simple eh?) let’s cover how each vendor is handling working with these table formats and see if they can play nicely with each other. The main difference is that only the table name and location of the table directory is stored in the catalog. In this table format, metadata about the table is kept “next” to the table much like Iceberg. For more information on Iceberg, please see this set of blog posts. A “ catalog ” in this instance is a placeholder for a table and the latest snapshot. There is typically a data and metadata directory. Iceberg stores metadata data “next” to the table data files on object storage. The most popular ones as of now are Apache Iceberg and Delta Lake. Second, let’s define the difference between a data catalog and a catalog which is used to store metadata about two different table formats. We’ll go with that definition, but let’s add governance which is basically access control. It helps data users find, understand, and trust the data they need to make informed decisions. įirst, Google Bard defines a data catalog as: a central repository of metadata that describes the data assets of an organization. In this blog post, I will compare the state of data catalogs in Starburst Galaxy, Databricks and Snowflake.
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