# resink.ai

> resink.ai is an AI first, cloud native, realtime data warehouse, leaner and more acicular alternative to Snowflake or Databricks.

## Docs

- [resink.ai](https://docs.resink.ai/index.md): AI-first, cloud-native realtime data warehouse with ResinKit SDK & UI.
- [Quickstart](https://docs.resink.ai/quickstart.md): Install ResinKit, connect, and run realtime analytics with Flink SQL.
- [ResinKit SDK User Guide](https://docs.resink.ai/resink-ai-tutorial/resinkit_sdk_user_guide.md)
- [Flink SQL UI](https://docs.resink.ai/resink-ai-tutorial/user-guide-flink-sql.md)
- [Data Sources UI](https://docs.resink.ai/resink-ai-tutorial/user-guide-sources.md)
- [Variables UI](https://docs.resink.ai/resink-ai-tutorial/user-guide-variables.md)
- [Basic Concepts](https://docs.resink.ai/rtdw/realtime_data_warehouse_basics.md): Core concepts: events, entities, aggregates, and strategies to preserve history.
- [S001: Entity Extraction and Archiving](https://docs.resink.ai/rtdw/workflows/S001_Entity_Extraction_and_Archiving.md): Extract entity properties from events and write to entity tables while preserving history.
- [S002: Raw Event Ingestion and Storage](https://docs.resink.ai/rtdw/workflows/S002_Raw_Event_Ingestion_and_Storage.md): Ingest raw events from Kafka and store them in Iceberg/Paimon tables with event-time partitions.
- [S003: Dimension Table Rehydration](https://docs.resink.ai/rtdw/workflows/S003_Dimension_Table_Rehydration.md): Rehydrate entity (dimension) tables from Iceberg/Paimon for fast lookups and enrichment in Flink.
- [S004: Feature Enrichment with Dimensions](https://docs.resink.ai/rtdw/workflows/S004_Feature_Enrichment_with_Dimensions.md): Enrich streaming events with entity (dimension) tables for real-time features and analytics.
- [S005: Event Aggregation (Session and Daily)](https://docs.resink.ai/rtdw/workflows/S005_Event_Aggregation_Session_and_Daily.md): Aggregate clickstream events to session-level and daily-level metrics using Flink SQL.
- [S006: Sessionization of Clickstream](https://docs.resink.ai/rtdw/workflows/S006_Sessionization_of_Clickstream.md): Derive user sessions from clickstream using session windows and output session-level facts.
- [S007: Build Fact Order Star Schema](https://docs.resink.ai/rtdw/workflows/S007_Build_Fact_Order_Star_Schema.md): Model and populate an orders fact table with conformed dimensions using Flink and Iceberg/Paimon.
- [S008: SCD Type 2 for Product and Pricing](https://docs.resink.ai/rtdw/workflows/S008_SCD_Type2_for_Product_and_Pricing.md): Maintain slowly changing product attributes and prices with history for point-in-time queries.
- [S009: Late Event Handling and Deduplication](https://docs.resink.ai/rtdw/workflows/S009_Late_Event_Handling_and_Deduplication.md): Handle late/duplicate events using watermarks, windowing, and row_number-based deduplication.
- [S010: Error Handling and DLQ Archiving](https://docs.resink.ai/rtdw/workflows/S010_Error_Handling_and_DLQ_Archiving.md): Route malformed events to a dead-letter queue (DLQ) and archive failures for auditing.
- [S011: CDC Ingest to Iceberg](https://docs.resink.ai/rtdw/workflows/S011_CDC_Ingest_to_Iceberg.md): Ingest change data capture (CDC) from OLTP into an Iceberg table for analytics and downstream processing.

## Optional

- [Home](https://resink.ai)
- [Community](https://discord.gg/UsfVqRsB)
- [Documentation](https://docs.resink.ai)