Amplitude is a hosted product analytics platform. Rawbbit is a self-hosted raw event pipeline. They solve different problems — here's how to tell which one fits.
If you've been looking at Amplitude and at self-hosted setups in the same browser session, you've probably noticed they don't quite match up. That's not an accident. They sit in different categories of tool.
This page is not a feature-by-feature scoreboard. Amplitude has years of product-analytics UI work behind it — cohort builders, funnels, retention dashboards, experimentation tools. Trying to match those one-for-one with a self-hosted pipeline misses the point.
Instead, this page covers what's actually different: the architecture, where the data lives, who owns the raw layer, and how to decide which approach fits your team.
Amplitude is a hosted product analytics platform. You send events to Amplitude's servers; their backend stores, processes, and aggregates them; you query through their web UI and a SQL-like interface they call Amplitude SQL. The platform optimizes for the analyst experience: visual cohort builders, drag-and-drop funnels, prebuilt retention views.
Rawbbit is a self-hosted raw event pipeline. You stand up the stack — collector, message broker, raw writer — inside your own cloud account. Events arrive over HTTP, get buffered through NATS JetStream, and land as partitioned Parquet files in object storage you control. From there, you query through your own warehouse layer (BigQuery external tables, or any tool that reads Parquet) and use any BI you already have.
These are complementary, not competing, in many real setups. Some teams run Rawbbit as the canonical raw layer and forward a subset of events into Amplitude for the product team. Others use one or the other but not both. The right question isn't "Rawbbit instead of Amplitude" — it's "which one does the job I actually need."
Where each system draws its boundaries, and where your data physically lives.
| Dimension | Rawbbit | Amplitude |
|---|---|---|
| Deployment model | Self-hosted. Pipeline components run as Docker containers inside your cloud account. | Hosted SaaS. Events go to Amplitude's infrastructure; you have no control over the pipeline runtime. |
| Where raw events live | In your object storage (GCS or any S3-compatible backend like SeaweedFS). Raw Parquet files are yours from the moment they land. | On Amplitude's servers. You can export, but raw export is a feature gated to higher tiers. |
| Data format | Apache Parquet, partitioned by date. Open format, readable by any modern warehouse, lake engine, or DataFrame library. | Amplitude's internal representation. Export gives you a defined export format, not portable raw events. |
| Query surface | BigQuery external tables over the raw Parquet layer. Standard SQL, your choice of BI tool (Metabase, Superset, anything that talks to BigQuery). | Amplitude UI plus Amplitude SQL. Tightly coupled to the platform. |
| Schema control | Schema lives in your code. Validation happens at the collector layer; storage is schema-on-read for raw, schema-on-write for any modeled tables. | Schema lives in Amplitude. Changes propagate through their data governance layer. |
| Vendor lock-in | Low. Raw Parquet files are yours by definition. The pipeline is open source under Apache 2.0. | Moderate to high. Event history is in Amplitude's hands; migration requires negotiated export. |
| Operational ownership | You operate the pipeline. Rawbbit provides the components and setup; cloud and infrastructure costs go to your provider directly. | Amplitude operates the pipeline. You operate your client integration. |
| Compliance posture | Data stays in infrastructure you control. EU data residency is automatic if you deploy in an EU region. | Events are processed by a third party. DPA, sub-processor list, regional hosting all apply. |
Amplitude is built around the idea that events are most useful once they've been organized into product-analytics concepts: users, sessions, cohorts, funnels, retention. The platform's value comes from the layer above raw events — the way it turns a stream into insight without an engineer in the loop.
Rawbbit is built around the idea that raw events should outlive whatever you're analyzing today. The pipeline preserves the original event shape in Parquet, partitioned by date, in your storage. What you do downstream — whether that's BigQuery dashboards, ad-hoc SQL, ML feature stores, or sending a subset onward to a product analytics tool — is open.
If your work depends on the cohort-and-funnel layer being immediately available without engineering effort, Amplitude is the right shape. If your work depends on the raw layer being durable, portable, and queryable on your own terms, that's Rawbbit.
A short framework based on team composition and stage, not feature checklists.
No. Rawbbit is a raw event pipeline, not a product analytics UI. If your team relies on visual cohort builders and prebuilt funnel views, you'll either keep using Amplitude for that layer or rebuild equivalent views in a BI tool like Metabase on top of the raw data.
Yes, and this is the recommended migration path. Your client sends each event to both endpoints; Amplitude continues to serve your existing dashboards while Rawbbit builds your raw archive in your own infrastructure. You can keep both running indefinitely or cut Amplitude later once you're confident in the new setup.
Cohorts and funnels are SQL queries on raw events. With raw events in BigQuery via the external table, any cohort or funnel that Amplitude can express can be written as SQL — and visualized in Metabase or a similar tool. The tradeoff is that the SQL is your responsibility, where Amplitude provides a UI.
Rawbbit is open source under Apache 2.0. The full pipeline — collector, raw writer, deploy scaffolding, the starter SQLMesh project — is on GitHub and inspectable. Amplitude is a closed platform with various export options.
If you are evaluating analytics alternatives, we can help you move to a portable raw-data-first setup.
See pricing details