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In the evolution of data lakehouses, 2026 is considered a watershed year. Previously, enterprises were forced to make "single-choice" decisions within the closed ecosystems of various cloud giants, making data migration difficult once stored. Now, **Open Table Formats**, represented by Apache Iceberg, have officially become the "universal language" for cross-platform interaction, completely ending expensive vendor lock-in. 1. What is the "common language" of the data world? Open Table Format (OPS) is a metadata standard that is not dependent on a specific engine. It sits between the underlying files (such as Parquet) and the upper-level computing engine, defining what a "table" actually looks like through a unified set of directory and manifest files. This means that regardless of whether your data is stored in AWS S3, Azure Blob, or a private cloud, and regardless of whether you use Snowflake for analysis today, switch the latest database to Databricks to run Spark tomorrow, or use Trino for real-time queries the day after, they all see the same logical table, and there is absolutely no need for time-consuming data format conversion. The reason why the open table format can end locking is that it achieves complete decoupling on three levels: Engine decoupling: It is "engine neutral". It is no longer a "Snowflake table" or a "Databricks table", but an "Iceberg table", which any standards-compliant engine can operate on as if reading and writing a local library. Storage decoupling: Data lifecycle management is no longer limited by expensive data warehouse storage, and enterprises can use inexpensive object storage to achieve petabyte-scale data governance. Autonomous Management: Through implicit partitioning and schema evolution , developers do not need to manually rewrite the partitioning logic, and the database can automatically adapt to business changes.
[Image comparing siloed data warehouse vendor lock-in versus open lakehouse architecture with interoperable formats] 3. The New Normal for the Industry in 2026The current industry consensus is that data formats must be public property, not private property. With major vendors embracing Iceberg and launching cross-platform metadata management standards such as Unity Catalog or Polaris , the friction costs of data exchange have dropped to an all-time low.
In summary, the Open Table format returns the choice to enterprises. It is not just a technical standard, but also a "declaration of data sovereignty": enterprises can finally freely change their analytics engines based on performance, cost, and AI capabilities without worrying about costly migration. Are you looking to understand how to migrate existing proprietary format data to Iceberg, or how to achieve efficient metadata synchronization in a multi-cloud environment?
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發表於 2026-1-27 12:58:40
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