offdata ai — agentic AI for data modelers and data engineers

Amazon Redshift

AI Amazon Redshift schema generator

Describe your domain in plain English. Ship a Redshift warehouse — DDL with the right DISTKEY, SORTKEY, and ENCODE choices, plus a complete dbt project.

ddl/redshift.sqlredshift sql
CREATE TABLE analytics.dim_customer (
  customer_sk   VARCHAR(64)   NOT NULL ENCODE ZSTD,
  customer_id   VARCHAR(64)   NOT NULL ENCODE ZSTD,
  name          VARCHAR(256)            ENCODE ZSTD,
  plan_id       VARCHAR(64)             ENCODE ZSTD,
  valid_from    DATE          NOT NULL  ENCODE AZ64,
  valid_to      DATE                    ENCODE AZ64,
  PRIMARY KEY (customer_sk)
)
DISTSTYLE ALL
SORTKEY (customer_id, valid_from);

CREATE TABLE analytics.fct_usage (
  usage_id      VARCHAR(64)   NOT NULL ENCODE ZSTD,
  customer_sk   VARCHAR(64)   NOT NULL ENCODE ZSTD,
  plan_id       VARCHAR(64)   NOT NULL ENCODE ZSTD,
  event_ts      TIMESTAMP     NOT NULL ENCODE AZ64,
  api_calls     BIGINT        NOT NULL ENCODE AZ64,
  PRIMARY KEY (usage_id)
)
DISTSTYLE KEY DISTKEY (customer_sk)
COMPOUND SORTKEY (event_ts, customer_sk);

OffDataAI is purpose-built for Amazon Redshift. Our generator emits Redshift-native DDL with the right distribution style (KEY / ALL / EVEN), compound or interleaved sort keys, and column-level compression encodings (ZSTD, AZ64) tuned to your data types. Small dimensions get DISTSTYLE ALL; large facts get DISTKEY on the dominant join column. From the same conversation, you also get a complete dbt project for dbt-redshift.

What OffDataAI generates

  • Redshift-native DDL

    DISTKEY, SORTKEY (compound + interleaved), ENCODE per column, late-binding views — never generic ANSI SQL.

  • Kimball, Data Vault 2.0, or 3NF

    Three paradigms supported. The generator emits the right distribution and sort strategies for each.

  • Full dbt project

    dbt_project.yml configured for dbt-redshift, sources, staging, marts (with dist + sort configs), schema tests, and seeds.

  • Compression chosen for you

    Per-column ENCODE chosen based on data type and cardinality — ZSTD for VARCHAR, AZ64 for numerics and timestamps.

Frequently asked questions

Can OffDataAI generate Amazon Redshift DDL from plain English?
Yes. Describe your business domain in plain English. OffDataAI's interview agent gathers grain, cardinality, and distribution hints, synthesizes a typed Intermediate Representation, and emits Redshift-native DDL with DISTKEY, SORTKEY, and column-level ENCODE settings.
Does OffDataAI choose DISTKEY and SORTKEY automatically?
Yes. The Redshift generator picks DISTKEY based on the most common join column (typically the customer or tenant key on facts) and SORTKEY based on the time-series column you described. You can override these in the IR before generation.
Does it support compound vs. interleaved sort keys?
Compound sort keys by default (the right choice for most analytical workloads). Interleaved is available as an option in the IR when you have multiple high-cardinality filter columns.
Does it support Kimball, Data Vault, and 3NF on Redshift?
Yes. All three paradigms are first-class on Redshift. The generator emits the right DIST/SORT strategies for each paradigm.
Does it generate a dbt project for Redshift?
Yes. OffDataAI emits a complete dbt project for Redshift — dbt_project.yml configured for dbt-redshift, sources, staging, marts (with dist + sort), schema tests, and seed CSVs.

Your data warehouse is one conversation away.

Describe your domain, or open one of 150+ production-grade templates. ERDs, DDL, and a complete dbt project — generated in under a minute.