OneLake
Every Fabric tenant has exactly one OneLake. Workloads store and read Delta or Iceberg tables in it, so one copy of data can serve Spark, SQL, and Power BI.
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Deletion Vector
A deletion vector is a bitmap that marks which rows of an immutable data file are deleted — cheap to write, a small tax on reads until the file is rewritten.
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Type Promotion
Type promotion widens a column’s type — int to long, float to double — without rewriting old files. See which widenings are allowed and why narrowing never is.
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Field ID
A field ID gives each column a permanent number, so a renamed or reordered column still lines up with old data files, and a new column never inherits old data.
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Table Format
A table format turns a pile of immutable files into a table: which files count right now, what the schema is, and how a change becomes visible all at once.
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Separating Storage, Compute, and Metadata
Splitting a warehouse replaces one product with five choices. See what object storage cannot do, how a table format fills the gap, and what copies cost.
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Partitioning, Compaction, and Table Maintenance
Lakehouse tables degrade through small files, drifting layouts, and old snapshots. See how sizing, pruning, compaction, and expiry work and how to validate their cost.
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Open Table Formats: Snapshots and Catalogs
A table format decides which files are the table, commits changes atomically, and lets readers keep a consistent snapshot. See how the mechanisms and their limits work.