Goals

Q4 2026 objectives

Objective 1: Open beta – Managed Warehouse serves inbound customers

Key results:

• Pricing is in place and applied to users – Anna SzellAnna Szell
• 10+ large customers run real business workloads on Managed Warehouse. We test-run an FDE onboarding or upkeep engagement – James GreenhillJames Greenhill
• HogLake deployment for all of PostHog is de-risked – Benjamin Knofe-ViderBenjamin Knofe-Vider
• Performance is good regardless of the use case – Guowei YangGuowei Yang
• DuckLake is shut down. All existing work runs on HogLake – Jakob HomanJakob Homan
• The schema is decided and in place – Jakob HomanJakob Homan
• Stricter limits are in place for ClickHouse modeling, with a smooth data modeling graduation and upsell flow – Eric DuongEric Duong

Objective 2: DevRel – improve product messaging internally and externally

Key results:

• Sales and Customer Success have demos – Eric DuongEric Duong
• The Managed Warehouse documentation on posthog.com is up to date – Eric DuongEric Duong
• We give external talks – James GreenhillJames Greenhill
• The database brand is established, including HogLake and the Trino fork – Elizabeth Epton

Handbook

Who are we building for?

Personas

• Primary Personas:
  • Data/Analytics Engineer
    • These are the engineers building and maintaining the whole data stack, and are also responsible for providing the best tooling for their company.
    • They want flexibility and control of every part of the stack to ensure correct reporting downstream.
  • Data Analysts/Product Managers (technical type)
    • They are responsible for providing insights for their teams/company. If a question can be answered by data, they will write complex SQL models to get to the answer.
    • Data analysts and product managers are the power-users of data modeling and business intelligence (BI). They have the desire and the time to go significantly deeper into the data.
• Limited focus:
  • Product engineer
• Not a focus but should be usable by:
  • All other engineers, e.g. they should have access to the data they need, and easily query it

Feature support by persona

Data/Analytics Engineers

What works today:

• Duckling provisioning and event data bootstrapping
• External source connector data landing in warehouse

What we need to ship:

• Tune compute allotment (scale up/down CPU and memory for workloads)
• Connect to modern data warehouse tooling
• Standard SQL interface (JDBC/ODBC drivers) for compatibility with existing pipelines
• Role-based access control and credential management
• Query performance monitoring and resource usage dashboards
• Support for custom materialized views and incremental models

Data Analysts/Product Managers

What works today:

• SQL querying of PostHog event data in Duckling
• "Golden tables" available in Product Analytics and Experiments

What we need to ship:

• Connect to BI tools (Metabase, Looker, Tableau, Power BI, Hex)
• Connect to data modeling tools (dbt)