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Rime Documentation

What is Rime?

Rime is a data platform that manages the operational complexity of a modern data stack. It sits between your data sources and Snowflake, handling extraction, infrastructure provisioning, transformation, orchestration, and governance through a single web interface.

Who Rime is for

Rime targets organisations running Snowflake-based data stacks that have outgrown manual management but want to reduce the engineering headcount required to keep everything running. Typical customers include:

  • Large New Zealand enterprises (TradeMe, Les Mills, Air New Zealand) with dedicated data teams spending most of their time on operational work rather than analysis
  • Mid-size companies with complex data stacks but smaller teams that cannot justify 5-10 data engineers for pipeline maintenance
  • Any organisation using Snowflake that wants to bring governance, monitoring, and infrastructure management under one roof

What Rime manages

A typical data stack without Rime looks like this:

  1. Extraction — tools like Stitch or Fivetran pull data from source systems into S3
  2. Ingestion — S3 events trigger Snowpipe to load raw data into Snowflake
  3. Transformation — dbt runs on a schedule to transform raw data through staging, warehouse, and mart layers
  4. Infrastructure — Terraform manages Snowflake roles, warehouses, databases, schemas, pipes, S3 buckets, IAM policies, and the connections between them
  5. Consumption — analysts connect Power BI or similar tools to the data mart layer

Each layer requires its own configuration files, deployment pipelines, monitoring, and expertise. Rime replaces the operational overhead of managing layers 1 through 4, while Snowflake remains your data warehouse and consumption tools remain your reporting layer.

How Rime fits your stack

Rime does not replace Snowflake, dbt, or Terraform. It manages them internally so you do not have to:

  • Infrastructure — you configure Snowflake resources (databases, schemas, warehouses, roles) and AWS resources (S3 buckets, IAM roles) through the Rime UI. Rime generates and applies Terraform internally. You never write or see HCL.
  • Extraction — you configure connectors to your source systems (databases, SaaS applications, REST APIs, files). Rime runs custom Rust-based connectors that extract data as Apache Arrow, write Parquet to S3, and trigger Snowpipe for ingestion.
  • Transformation — you select a modelling methodology (Kimball or Data Vault), choose source tables, and configure dimensions, facts, or hubs. Rime generates and executes dbt projects internally. You never write SQL or manage dbt files.
  • Orchestration — you build pipelines as visual DAGs with extraction, infrastructure, transformation, and validation steps. Rime schedules and executes them with retry policies and real-time progress tracking.
  • Governance — Rime applies a masked-by-default security model. All columns are masked until explicitly classified and unmasked per role. PII detection runs automatically with New Zealand and Australia-specific patterns.

Scope boundary

Rime covers everything from your data sources up to Snowflake’s query interface. Snowflake itself is the destination — Rime configures it but does not replace it. The consumption layer (Power BI, Tableau, or similar) is outside Rime’s scope.

Next steps