Accelerate search queries with full-text search indexes on Databricks

2026-06-16 · Source: Databricks · Field: Technology & Digital — Data Science & Analytics, Cloud Computing & IT Infrastructure · Depth: Intermediate, short

Summary

Databricks has announced the Beta release of full-text search indexes, available on Databricks Runtime 18.2, designed to accelerate substring and keyword queries on large text columns. This solution addresses the challenge of slow text searches across terabytes or petabytes of data, which often forces teams into workarounds like external search systems. Full-text search indexes are ideal for high-cardinality lookups in scenarios such as log analytics, SIEM, trust and safety investigations, and compliance auditing. The index works by tokenizing text content and building a compact lookup structure, allowing the query engine to read only a fraction of the data. This architecture ensures zero impact on write performance, automatic query optimization, and guaranteed correctness, supporting Unity Catalog managed Delta and Iceberg tables. A customer observed over 100x faster substring searches on a petabyte-scale table.

Key takeaway

For Data Engineers or MLOps Engineers managing large text datasets on Databricks, implementing full-text search indexes can dramatically improve query performance. If you are struggling with slow substring or keyword searches in logs, security data, or compliance records, consider adopting this Beta feature. It allows your existing queries to run significantly faster, potentially over 100x, without modifying your application logic or impacting write operations. Plan to test it on Databricks Runtime 18.2 to streamline your analytical workflows.

Key insights

Databricks full-text search indexes accelerate substring and keyword queries on large text columns by indexing tokens.

Principles

• Indexes are maintained asynchronously, preserving write performance.
• Query correctness is guaranteed even with stale indexes.
• Full-text indexes complement physical data clustering.

Method

Create a search index on specified text columns; the query engine automatically uses it to skip irrelevant files during SEARCH queries, accelerating lookups.

In practice

• Accelerate log analytics and SIEM investigations.
• Speed up content moderation searches in trust and safety.
• Expedite compliance auditing for specific terms.

Topics

• Full-text Search
• Databricks Runtime
• Delta Lake
• Iceberg Tables
• Log Analytics
• SIEM
• Unity Catalog

Best for: CTO, VP of Engineering/Data, Data Engineer, MLOps Engineer, AI Architect

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Editorial summary, takeaway, and curation by AIssential. Original article published by Databricks.