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Iceberg management made simple.

Ryft automatically maintains and optimizes your Iceberg tables for peak query performance and cost, by constantly analyzing usage patterns.

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How does it work?

Ryft dynamically adapts to each table's unique workloads, and gives you full visibility into your entire lakehouse - all from a single pane.

Whatever the use-case, we support it.

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Batch Processing

Adaptive compaction keeps your nightly jobs on schedule.
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Streaming

Peak real-time query performance, with low storage overhead
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CDC

Efficiently merges change-data streams without commit conflicts.
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High Throughput

Maintain consistent performance at petabyte scale.
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1000s of tables

Centrally auto-optimizes thousands of tables.
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Multiple query engines

Keep your Iceberg lakehouse optimized, no matter the query engine you use.

Unified Visibility

Stay on top of your lakehouse, and make smarter decisions, with a single pane on your entire lakehouse.
Cross-engine view tab icon
Cross-engine view
Columns usage tab icon
Columns usage
Storage visibility tab icon
Storage visibility
Query explorer tab icon
Query explorer
Automatic Insights tab icon
Automatic Insights
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Unused Assets

Cross-engine view

View usage from all query engines in one place. Understand how data is created and used across Spark, Trino, Snowflake, and more.

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Columns usage

Know exactly how each column’s used, how often, and by whom. Cut dead weight, tighten schemas, and boost performance.

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Storage visibility

Get a granular view on your partitions, data files and metadata. See which tables have skewed partitions, bloated snapshots and exploding metadata.

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Query explorer

Search and filter queries across engines. See who’s running what, and quickly spot issues or tuning opportunities.

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Automatic Insights

Get instant insights into your Iceberg table layout - spot small files, partition skew, sort order issues, and more, without manual digging.

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Unused Assets

Find tables, and columns and snapshots no one uses. Cut clutter, lower costs, and reduce compliance risk.

tab illustration
tab illustration
Cross-engine view tab icon
Cross-engine view
View usage from all query engines in one place. Understand how data is created and used across Spark, Trino, Snowflake, and more.
tab illustration
Cross-engine view tab icon
Columns usage
Know exactly how each column’s used, how often, and by whom. Cut dead weight, tighten schemas, and boost performance.
tab illustration
Cross-engine view tab icon
Storage visibility
Get a granular view on your partitions, data files and metadata. See which tables have skewed partitions, bloated snapshots and exploding metadata.
tab illustration
Cross-engine view tab icon
Query explorer
Search and filter queries across engines. See who’s running what, and quickly spot issues or tuning opportunities.
tab illustration
Cross-engine view tab icon
Automatic Insights
Get instant insights into your Iceberg table layout - spot small files, partition skew, sort order issues, and more, without manual digging.
tab illustration
Cross-engine view tab icon
Unused Assets
Find tables, and columns and snapshots no one uses. Cut clutter, lower costs, and reduce compliance risk.