How Much Does an Analytics Platform Cost on AWS, Azure, or GCP?
An analytics platform costs $50-$200/mo at 1M events/month and scales to $5,000-$15,000/mo at 1B events/month. Self-hosting becomes cheaper than managed tools like Mixpanel or Amplitude above roughly 100M events per month.
Building an analytics or business intelligence platform requires data ingestion, warehousing, query engines, and visualization. Costs depend on data volume, query concurrency, and retention policies. Use our calculator to compare analytics infrastructure costs across AWS, Azure, and GCP.
Analytics Platform Components
A production analytics platform requires a data ingestion pipeline (Kinesis, Event Hubs, or Pub/Sub) for capturing events, a data warehouse (Redshift, Synapse, or BigQuery) for analytical queries, a query engine for ad-hoc exploration, a caching layer (Redis or Memcached) for accelerating dashboard queries, an API layer for programmatic data access, and a visualization frontend for dashboards and reports.
Build vs Buy Analytics
Managed analytics services like Mixpanel and Amplitude cost $0–$2,000/month depending on event volume and features. Self-hosted analytics on cloud infrastructure costs more at small scale but becomes significantly cheaper above approximately 100M events per month. Self-hosted also gives you full data ownership, custom query flexibility, and no vendor lock-in on your analytics data — a critical consideration for data-driven companies.
Analytics Platform Costs by Event Volume
At 1M events/month, a basic analytics setup costs $50–$200/month with a small warehouse and minimal ingestion. At 10M events/month, expect $200–$800/month with dedicated streaming ingestion and moderate query compute. At 100M events/month, costs range from $1,000–$4,000/month. At 1B events/month, infrastructure reaches $5,000–$15,000/month. Storage is relatively cheap at every tier; compute for real-time aggregations and complex analytical queries is the expensive component.
Key Cost Factors
- Data warehouse: Analytical query processing
- Streaming ingestion: Event capture pipeline
- Object storage: Raw event archival
- Caching: Dashboard query acceleration
- API compute: Programmatic data access layer
- Data transfer: Cross-service communication costs
Frequently Asked Questions
How much does an analytics platform cost on AWS vs Azure vs GCP?
At 1M events/month, a basic analytics setup costs $50-$200/month with a small warehouse and minimal ingestion. At 10M events/month, expect $200-$800/month with dedicated streaming ingestion. At 100M events/month, costs run $1,000-$4,000/month, and at 1B events/month, infrastructure reaches $5,000-$15,000/month. Storage is relatively cheap at every tier on all three providers; compute for real-time aggregations is where the bill diverges.
Is a managed analytics tool or self-hosted platform cheaper?
Managed analytics services like Mixpanel and Amplitude cost $0-$2,000/month depending on event volume and features, and are usually cheaper at small scale. Self-hosted analytics on cloud infrastructure costs more upfront but becomes significantly cheaper above roughly 100M events per month, while also giving full data ownership and no vendor lock-in — an important factor for data-driven companies with compliance requirements.
What drives the cost of an analytics platform?
Compute for real-time aggregations and complex analytical queries is the most expensive component, not storage, which stays relatively cheap at every tier. The data warehouse handling analytical queries and the streaming ingestion pipeline (Kinesis, Event Hubs, or Pub/Sub) capturing events are core costs, alongside a caching layer for accelerating dashboard queries and an API layer for programmatic data access.
How accurate are these analytics platform cost estimates?
Estimates use published on-demand list prices for AWS, Azure, and GCP data warehouse, streaming, and compute services in US regions, last verified 2026-07-15. Query complexity and dashboard refresh frequency significantly affect real compute costs beyond what a per-event estimate can capture. See /methodology for the full assumptions.