Analytics Accelerator
=====================

The Postgres Analytics Accelerator (PGAA) transforms Postgres into a
high-performance analytical engine. By integrating vectorized execution
and open table formats, PGAA allows you to run complex OLAP queries
directly on your data lake without leaving the Postgres ecosystem.

Use the following resources to understand the foundation of the
accelerator and prepare your environment for production workloads.

- :ref:`Analytics Accelerator quickstart guide <Analytics Accelerator quickstart guide>`  : A step-by-step guide to install PGAA, create a storage
  location and read a table from our sample benchmark datasets.

- :ref:`Analytics Accelerator architecture <Analytics Accelerator architecture>`  : A deep dive into the decoupled compute and storage
  model. Learn how the PGAA extension interacts with Seafowl (the
  vectorized engine), and object storage providers like S3, GCS, and
  Azure Data Lake Storage.

- :ref:`Concepts <Concepts>`  : Explore the fundamental principles of PGAA, including
  vectorized execution, columnar storage, and the difference between the
  DirectScan and CompatScan execution paths.

- :ref:`Analytics Accelerator compatibility <Analytics Accelerator compatibility>`  : A detailed matrix of supported Postgres versions,
  operating systems, and cloud provider availability.

- :ref:`Known issues <Known issues>`  : A transparent list of current limitations, unsupported
  cases, and active bugs we are currently addressing.

.. toctree::
  :maxdepth: 3

  overview--quick_start
  overview--architecture
  overview--concepts
  overview--known_issues
  overview--compatibility