Apache Polaris Catalog Architecture

Overview & Architectural Motivation

Apache Polaris (incubating) is an open source catalog for Apache Iceberg tables based on the open Iceberg REST Catalog specification. Originally open-sourced by Snowflake and donated to the Apache Software Foundation, Polaris provides a vendor-neutral, centralized control plane for table discovery, access governance, and security across multi-cloud environments.

Without an open catalog standard, organizations using Apache Iceberg were forced to either maintain proprietary catalog services (such as AWS Glue or Databricks Unity Catalog) or manage self-hosted Hive Metastore clusters. Proprietary catalogs frequently lock security controls and advanced table features inside a single vendor platform.

Polaris implements the open Iceberg REST catalog specification directly. It decouples security and catalog services from proprietary vendors, allowing any compatible compute engine to query and write Iceberg tables with centralized access policies.

Architecture & System Flow

Internal Mechanics & Specifications

Apache Polaris operates via the standardized Iceberg REST catalog interface:

Open REST Catalog Standard

Polaris exposes standard REST API endpoints for table management, namespace hierarchy, and snapshot commits. Any engine with an Iceberg REST catalog client connects to Polaris without custom drivers or vendor-specific plugins.

Role-Based Access Control (RBAC)

Polaris manages hierarchical security models using Principal Roles and Catalog Roles. Permissions (such as TABLE_READ, TABLE_WRITE, and TABLE_DROP) are assigned cleanly to catalog roles and granted to technical service principals or identity groups.

Storage Credential Vending

One of the most powerful capabilities of Polaris is automated credential vending. Instead of granting analytical engines broad read/write access to underlying object storage buckets, engines authenticate exclusively to Polaris. Upon validating authorization, Polaris requests a short-lived, down-scoped security token from the cloud provider (AWS STS, Azure SAS, or GCP STS) limited strictly to the physical directory path of the requested table. The engine receives the token and reads the files directly from storage.

Atomic Commits and Concurrency

Polaris acts as the atomic commit arbiter. When an engine writes an update, it submits a commit request to Polaris containing the previous snapshot ID and the proposed new snapshot ID. Polaris ensures compare-and-swap serializability, rejecting conflicting commits and prompting the engine to retry.

Role in the Open Lakehouse and AI Architecture

Apache Polaris provides the universal governance backbone of an Open Lakehouse.

In modern enterprise architectures, data is rarely processed by a single query engine. Dremio executes interactive SQL queries, Spark performs heavy batch transformations, and Python jobs run feature engineering. Polaris ensures all engines see the exact same catalog hierarchy, permissions, and table states without duplicating access rules across multiple tool consoles.

For AI agents and agentic pipelines, Polaris provides a secure, auditable gateway. Agents operating through Model Context Protocol (MCP) servers authenticate against Polaris to discover available tables and receive time-delimited access credentials, ensuring that AI tools respect enterprise data boundary controls.

Ecosystem Interoperability & Open Interfaces

Polaris integrates directly with all components of open architecture:

• Authoritative catalog implementation for Apache Iceberg tables.
• Native interoperability with Dremio, Apache Spark, Trino, Flink, and PyIceberg clients.
• Multi-cloud storage support across Amazon S3, Azure ADLS Gen2, and Google Cloud Storage.
• Compatible with OAuth2 identity providers and enterprise OIDC identity systems.

Production Engineering Considerations

Production considerations for deploying Apache Polaris

Stateless Service Deployment

Polaris is designed as a stateless application layer backed by relational persistence (such as PostgreSQL) for metadata storage. Deploy Polaris across multiple container instances behind a high-availability load balancer.

Credential TTL Tuning

Configure credential vending time-to-live (TTL) to balance security and long-running query stability. A TTL of one hour is standard, with client engines refreshing credentials automatically during extended operations.

Catalog Role Hierarchy

Structure catalog roles logically by domain or data product rather than creating one-off permissions per user, keeping access policies maintainable over time.