Overview

e6 Ingestion Engine pipelines are written in SQL. The dialect is based on Apache DataFusion - a well-supported SQL engine built on Apache Arrow - and extended with streaming-specific constructs like windows, watermarks, and event-time joins.

If you've used other SQL engines (Postgres, DuckDB, Spark SQL, Flink SQL), most of what you already know carries over. The sections below cover the pieces that are either specific to e6 Ingestion Engine or particularly important for streaming.

Start with the Quick Start, then use the reference sections below in navigation order.

Core reference

• DDL Statements - CREATE TABLE for connection tables, CREATE VIEW, and the WITH options used to configure connectors.
• Basic Queries - the basic query syntax, including projections, filtering, UNNEST, and subqueries.
• SQL Data Types - the primitive and complex types supported by e6 Ingestion Engine, and how they map to underlying Rust types.

Streaming

• Joins - stream-stream joins (windowed and interval), lookup joins against external systems, and the semantics of each.
• Stateful Queries - working with update streams (CDC-style data), including Debezium-formatted inputs and outputs.
• Streaming Windows - tumbling, sliding, and session windows for time-bucketed aggregations.

Functions

• Scalar Functions - math, string, JSON, time, array, struct, regex, hashing, and more.
• Aggregate Functions - sum, count, avg, array_agg, and other functions usable in GROUP BY queries.
• Window Functions - OVER-clause analytical functions like row_number, rank, and lag/lead.

For user-defined functions in Rust or Python, see the UDF docs.