Solutions
Analytics Architecture That Scales
We don't prescribe one-size-fits-all solutions. We help you choose and implement the right architecture for your scale, team, and business questions.
No Vendor Lock-in
All tools we implement are open-source or provide full data export. Your data is yours—migrate anytime without losing history or paying extraction fees.
Transparent Data Processing
Know exactly how your data is collected, stored, and processed. No black boxes, no hidden algorithms—just clear, auditable data pipelines you can inspect and understand.
Full Data Ownership
Self-host in your infrastructure or use managed services—either way, you control access, retention, and deletion. Meet compliance requirements without compromise.
Technology Stack
Open-Source Tools We Support
We specialize in modern, open analytics tools that give you full ownership of your data—no vendor lock-in, no hidden costs, and complete transparency in how your data is processed.
PostHog
Product analytics, session replay, feature flags, A/B testing—all in one open-source platform.
ClickHouse
Column-oriented OLAP database that runs analytical queries on billions of rows in milliseconds.
Jitsu
Open-source event collection that routes data to any destination with schema enforcement.
Matomo
Privacy-focused web analytics with full data ownership—self-hosted or cloud, GDPR compliant by design.
Databuddy
Cookieless analytics with zero consent banners—3KB script, real-time data, 100% GDPR compliant by design.
Reference Architecture #1
PostHog-First Product Analytics
The fastest path to product insights. PostHog handles event collection, storage, and analysis in one platform. Ideal for teams that want powerful analytics without managing infrastructure.
When to Use
- Primary focus is product analytics (funnels, retention, cohorts)
- Team size under 50 or early-stage startup
- Want feature flags and A/B testing in same platform
- Don't need complex cross-platform marketing attribution
Pros
- Single platform for analytics, experiments, and feature flags
- Fast time to value (days, not weeks)
- Built-in session recording and heatmaps
- Self-hosted option for data control
Tradeoffs
- Marketing attribution requires additional tooling
- Complex SQL queries need PostHog's SQL interface
- Scale limits depend on hosting option
Reference Architecture #2
ClickHouse Warehouse-First
Maximum flexibility and query power. All event data flows through Jitsu into ClickHouse, where you can run any SQL query, model data with dbt, and connect any BI tool. Ideal for data teams that want full control.
When to Use
- Need to join event data with other sources (CRM, billing, etc.)
- Have analysts who prefer SQL over UI-based tools
- Require custom attribution models or complex aggregations
- Processing 100M+ events per month
Pros
- Full SQL access to all event data
- Join with any other data source
- Sub-second queries on massive datasets
- Complete data ownership and control
Tradeoffs
- Requires data engineering resources
- Longer time to first insight
- Need to build/choose separate tools for experiments
Reference Architecture #3
Hybrid Marketing + Product Stack
Best of both worlds. PostHog handles product analytics and experiments while ClickHouse serves as the central warehouse for marketing attribution, cross-platform analysis, and executive reporting.
When to Use
- Product and marketing teams both need analytics
- Require multi-touch attribution across channels
- Need finance-reconciled metrics for reporting
- Want product analytics UI plus warehouse flexibility
Pros
- PostHog's UX for PMs and product analysts
- Full SQL power for marketing and finance
- Single source of truth for cross-team metrics
- Experiments in PostHog, attribution in warehouse
Tradeoffs
- Two systems to maintain
- Requires data modeling to unify definitions
- Higher infrastructure cost
Reference Architecture #4
Databuddy Zero-Cookie Analytics
Privacy by design. Databuddy provides accurate analytics without cookies, consent banners, or GDPR concerns. Ideal for privacy-conscious organizations that want to eliminate consent friction while maintaining full analytical capabilities.
When to Use
- Privacy is a core requirement or brand value
- Want to eliminate cookie consent banners entirely
- Operating in strict regulatory environments (EU, healthcare)
- Concerned about ad-blocker impact on data accuracy
Pros
- No cookie consent banners—zero friction for users
- 100% GDPR/CCPA compliant by design
- Immune to ad-blockers and privacy browsers
- Ultra-lightweight (3KB vs 45KB for GA4)
Tradeoffs
- No persistent user identification across sessions
- Newer platform with smaller ecosystem
- Session replay requires separate configuration
Data Quality
Governance & Privacy-Aware Measurement
Every architecture we implement includes data quality controls and privacy compliance.
Schema Governance
Event schemas are documented, validated, and enforced. No more mystery properties or inconsistent naming that breaks reports.
Data Validation
Automated checks catch tracking issues before they corrupt your data. Alerts notify the right people when something breaks.
Privacy Compliance
GDPR, CCPA, and cookie consent built in from the start. PII handling, retention policies, and deletion workflows are part of the architecture.
Which Architecture Is Right for You?
The best architecture depends on your team, scale, and business questions. Let's discuss your situation and design the right solution.