Composable warehouse-native customer data platform

Yes, this approach is called a Composable CDP (or warehouse-native CDP) , and it directly replaces monolithic black-box CDPs by building customer profiles and syncing data straight out of your existing cloud data warehouse.hightouch.com+2

Instead of forcing you to pipe your data into a vendor's proprietary database, a composable CDP unbundles the core functions of a traditional CDP—collection, storage, identity resolution, modeling, and activation—so your data warehouse remains the single source of truth.hightouch.com+1

How the Composable CDP Stack Works

A composable CDP relies on specialized best-of-breed tools mapped to distinct layers of your existing data ecosystem rather than a single locked-in vendor.hightouch.com

• Storage Layer (Your Warehouse): SnowflakeSnowflake, Google BigQueryGoogle BigQuery, DatabricksDatabricks , or Amazon RedshiftAmazon Redshift store all raw and modeled customer data.hightouch.com
• Collection Layer: Event stream tools like RudderStackRudderStack or JitsuJitsu capture behavioral and clickstream data and load it directly into your warehouse instead of an external silo.
• Modeling & Identity Resolution Layer: Transformation tools like dbt (Data Build Tool)dbt (Data Build Tool) clean data, join disparate touchpoints, and stitch together unified customer profiles natively inside your warehouse.
• Activation Layer (Reverse ETL): Tools like HightouchHightouch or CensusCensus query those modeled profiles in your warehouse and sync them downstream to marketing, sales, and support tools (like Salesforce, Facebook Ads , or Klaviyo).hightouch.com+1

Traditional CDP vs. Composable CDP

If you want to map out a migration or build plan, let me know:

• What cloud data warehouse are you currently using (e.g., Snowflake, BigQuery)?
• Are you already using dbt for data modeling?
• Which downstream tools (CRMs, ad platforms) do you need to sync audiences to first?

Yes. The category you’re looking for is generally called a composable CDP or warehouse-native CDP: the warehouse/lakehouse remains the system of record, while specialized tools provide collection, identity, audience building, and activation around it.

The architecture looks roughly like:

Your sources → your warehouse/lakehouse → identity + customer models → activation tools

rather than:

Your sources → vendor CDP database → vendor identity/audience layer → warehouse + downstream tools

RudderStack describes the distinction explicitly: in a warehouse-native model, identity, traits, governance, and activation-ready data remain anchored in your warehouse rather than in a proprietary CDP database.www.rudderstack.com

The main options I'd investigate

Hightouch explicitly positions itself as a composable CDP sitting on existing Snowflake, BigQuery, Databricks, or Redshift infrastructure, with the warehouse remaining the source of truth.hightouch.com+1

RudderStack is particularly interesting if collection is part of the problem, not just activation: it combines event collection with warehouse-native identity/profile modeling and downstream activation.www.rudderstack.com

Snowplow takes an even more infrastructure-oriented approach: behavioral events are collected into your data platform, with identity resolution/modeling available through warehouse/dbt-based components.snowplow.io+1

And Census is now Fivetran Activations following Fivetran's acquisition; it focuses heavily on reverse ETL—moving governed warehouse data into CRMs, marketing platforms, and other operational systems.fivetran.com

The important distinction

I'd separate "composable CDP" into two layers:

1. Customer data infrastructure

• SDK/event collection
• schema enforcement
• identity stitching
• raw behavioral data
• customer 360 / feature models
• consent and governance

2. Customer activation

• audience builder
• CRM sync
• Braze/marketing activation
• advertising audiences
• journeys
• real-time APIs

You don't necessarily need one vendor for both.

A very clean architecture could therefore be:

Snowplow/RudderStack → Snowflake/BigQuery/Databricks → dbt → Hightouch/Fivetran Activations → Salesforce/Braze/etc.

That gives you the strongest version of the "we own our data" principle: customer identity and audience definitions are tables/code in your environment, not proprietary objects trapped inside the CDP.

Snowplow actually publishes this sort of modular architecture, including a pattern where behavioral data is collected and processed in the warehouse and then reverse-ETL'd into operational systems.snowplow.io

One caveat

"Warehouse-native" doesn't automatically mean zero vendor lock-in. The things I'd scrutinize in a vendor evaluation are:

• Does the vendor retain a copy of your customer data?
• Where does the identity graph physically live?
• Can you export all identity mappings and audience definitions?
• Is identity logic transparent/version-controlled?
• Can you replace the activation vendor without rebuilding your customer model?
• Can the system handle real-time use cases, or only warehouse-refresh latency?
• Does the vendor require its own proprietary event schema?
• What happens if its service is unavailable?
• Can your data team operate the core system without the vendor UI?

Those questions distinguish a genuinely composable architecture from a traditional CDP that simply markets itself as composable.

If your goal is specifically "we already have Snowflake/Databricks/BigQuery and absolutely do not want another customer-data silo," I'd shortlist Hightouch, RudderStack, Snowplow, and Fivetran Activations—but for different pieces of the stack rather than treating them as interchangeable CDPs.snowplow.io+1

If you tell me your warehouse (Snowflake/BigQuery/Databricks/etc.), current event collector, and destinations (e.g. Salesforce, Braze, HubSpot, ads), I can sketch a concrete composable-CDP architecture and compare the likely vendors/cost/lock-in tradeoffs.

Yes. What you're looking for is generally called a composable CDP or warehouse-native customer data platform. These platforms sit on top of your existing data warehouse, letting you build customer profiles, segment audiences, and activate data across marketing and sales tools without moving your entire customer database into a proprietary CDP.

The key advantage is that your warehouse remains the source of truth: your team retains control of the data, SQL models, and governance, while the CDP supplies the tools to make that data useful to business teams.hightouch.com+2

Three options worth evaluating

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1. Hightouch

(Best starting point)

Best for: Marketing teams that need self-service audience building and campaign activation.

• Runs on top of Snowflake, Databricks, BigQuery, Redshift, and other supported warehouses.
• Offers audience segmentation, identity resolution, customer profiles, and journey orchestration.
• Keeps core customer data in your warehouse rather than maintaining a separate copy of customer profiles.hightouch.com+2

Explore:Hightouch Composable CDP

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2. RudderStack

Best for: Engineering-led teams that want control over data collection and customer-data pipelines.

• Collects website, app, and server-side behavioral events.
• Supports identity resolution and customer profiles built in your warehouse.
• Provides event streaming, transformations, and activation integrations, with an open-source foundation.www.rudderstack.com+1

Explore:RudderStack documentation

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3. ActionIQ

Best for: Large enterprises with complex customer journeys and sophisticated segmentation needs.

• Offers a warehouse-only architecture that pushes queries down to your existing warehouse.
• Provides enterprise audience management, identity resolution, and customer journey capabilities.
• Has multiple deployment models, so you must explicitly select and verify the warehouse-only configuration if avoiding a separate data store is essential.aws.amazon.com+2

Explore:ActionIQ architecture overview

How they compare

Feature descriptions are based on vendor documentation; exact capabilities vary by plan and deployment.hightouch.com+2

What to check before choosing

A composable CDP reduces data duplication, but it doesn't eliminate vendor dependency altogether. Your activation workflows, connectors, identity logic, and orchestration may still depend on the vendor.

I would validate five things in a proof of concept:

• Data residency: Does customer-level data stay in your warehouse, including identity graphs, audience memberships, and derived attributes?
• Portability: Can you export configurations, SQL models, audience definitions, and identity rules if you leave?
• Warehouse compatibility: Does it support your exact platform and deployment architecture?
• Activation: Can it sync to your CRM, advertising, email, and customer engagement tools?
• Real-time requirements: Does it support event-triggered personalization, or primarily scheduled warehouse queries?

My recommendation

Start with Hightouch if your priority is empowering marketers to build audiences and launch campaigns without creating another customer-data silo. Evaluate RudderStack alongside it if owning your collection pipelines and event infrastructure is equally important. For a large enterprise with complex journey orchestration, include ActionIQ.

To narrow this to the best fit, I can compare options for your warehouse or build a vendor evaluation checklist.