We architect and implement composable customer data platforms — Snowflake or Databricks as the warehouse, Hightouch or Segment for activation, connected to Braze and the rest of your engagement stack. No separate monolithic CDP license required.
We work across every layer of the composable stack — warehouse, transformation, activation, and identity resolution.
We design and implement the Snowflake or Databricks foundation your CDP sits on — schema design, ingestion pipelines from every source system, and the modeling layer that turns raw data into clean customer profiles.
We define and implement the matching logic that turns fragmented records — anonymous web visitors, app users, email subscribers — into one accurate, unified customer profile per person.
We implement Hightouch or Segment to sync your warehouse-modeled audiences out to every downstream tool that needs them — no data duplicated into a separate proprietary CDP database.
We connect your unified customer data to Braze (or your engagement platform of choice) so behavioral segments actually trigger real campaigns — not just sit in a dashboard.
We build access controls, consent management, and audit logging into the data model from day one — not bolted on after a compliance issue forces the conversation.
We monitor sync reliability, audit segment accuracy, and adjust the architecture as your data sources and activation needs change over time — CDPs need maintenance, not just a launch.
We map your current data sources, existing tools, and real activation needs before recommending any specific architecture.
We design the warehouse schema, identity resolution rules, and activation destinations specific to your actual use cases.
We build the pipeline — ingestion, modeling, reverse ETL sync, and activation tool connections — in a staged, testable rollout.
We monitor, audit, and adjust the system as your data sources and business needs evolve — not a one-time handoff.
An honest comparison of your three realistic options.
Full explanation of the composable model: What Is a Customer Data Platform? →
We'll audit your current data sources and tools and tell you plainly whether a composable CDP is the right move — or whether something simpler solves your actual problem.
“Rackwave Technologies has significantly improved our marketing performance while providing reliable cloud services. We’ve been using their solutions for a while now, and the experience has been seamless, scalable, and results-driven.”
David Larry
Founder & CEOCommon questions about CDP consulting with Rackwave Technologies.
Our primary approach is composable — building on your existing or planned data warehouse (Snowflake or Databricks) with reverse ETL for activation, since this avoids vendor lock-in and reuses infrastructure you likely already need for analytics regardless. That said, for businesses without warehouse ambitions or needing the fastest possible basic setup, a packaged CDP product can be the right call, and we'll tell you honestly when that's the better fit for your specific situation rather than defaulting to our preferred architecture.
Composable architecture avoids the separate CDP platform license fee, since you're paying for warehouse compute (which many companies already have for analytics) plus a reverse ETL tool, rather than an additional dedicated CDP product on top. The real cost comparison depends on your specific data volume and existing infrastructure, but for organizations already running Snowflake or Databricks for other purposes, the marginal cost of adding CDP capability is often meaningfully lower than licensing a standalone CDP product.
No — if you don't have a warehouse yet, implementing one is part of the engagement, not a prerequisite you need to arrange separately. We'll help you choose between Snowflake and Databricks based on your actual analytics and data science needs, then build the CDP capability on top of that foundation as part of the same project.
A skilled data engineer can build parts of this, but composable CDP implementation specifically requires expertise across multiple layers — warehouse architecture, identity resolution logic, reverse ETL tooling, and activation platform integration (particularly Braze, which we implement extensively) — that rarely lives in one generalist hire. We bring that combined expertise as a team rather than requiring you to assemble and manage multiple specialists.
Yes, this is one of our core strengths — we implement Braze extensively as an engagement platform, and connecting warehouse-modeled audience data into Braze via reverse ETL is a common, well-understood part of our composable CDP engagements. If Braze is your engagement platform, this integration is a natural fit for how we already work.
A focused initial implementation — one or two priority data sources, core identity resolution, and a handful of activation destinations like Braze — can often be delivered in a small number of weeks. A comprehensive implementation across many data sources and destinations, with more sophisticated identity resolution and governance requirements, typically takes longer and is scoped based on your specific complexity during the audit phase.
Both — initial implementation is the first phase, but data sources change, new activation tools get added, and segment definitions need periodic review as your business evolves. We offer ongoing optimization and managed services specifically because CDPs that aren't maintained gradually become less accurate, and we'd rather build something that stays reliable than hand off a system that degrades within months.
Because the composable approach keeps your data in your own warehouse (Snowflake or Databricks) rather than a proprietary CDP vendor's system, you retain full ownership and access regardless of who's implementing on top of it. This is one of the genuine architectural advantages of composable over packaged CDP products — there's no data migration required if you change implementation partners, since the data was never locked into our systems in the first place.
Sometimes, yes — and we'll tell you that directly during the assessment rather than push an unnecessary implementation. If your customer data lives in one or two tools that already integrate well, or your data volume is genuinely small, a full CDP implementation may not be the right investment yet. We'd rather have an honest conversation about whether you actually need this now than sell a project that doesn't serve your real situation.
Start with a free assessment — we'll look at your actual data sources, existing tools, warehouse situation (or lack of one), and real activation needs, then give you a straight recommendation on whether composable architecture, a packaged CDP product, or something simpler entirely fits your specific situation best.