Propel
Propel is an API-first data platform for embedded analytics that lets developers build fast, customer-facing metrics and dashboards by querying data through a GraphQL API with sub-second latency.
Score Breakdown
⚙ Agent Friendliness
🔒 Security
OAuth 2.0 with client credentials and policy-based multi-tenant isolation is a strong security model for embedded analytics. Short-lived tokens reduce credential exposure. Policy enforcement is server-side.
⚡ Reliability
Best When
You need to embed customer-facing analytics in your SaaS product with sub-second query performance and want a GraphQL API rather than building and maintaining your own OLAP stack.
Avoid When
Your analytics needs are entirely internal (not customer-facing) or you already have a mature data warehouse like Snowflake/BigQuery with a BI tool in front of it.
Use Cases
- • Query aggregated business metrics (counts, sums, averages) filtered by customer ID to power per-tenant analytics dashboards embedded inside a SaaS product
- • Push time-series event data to Propel via HTTP or Kafka and make it immediately queryable through the GraphQL API without managing a data warehouse
- • Build a real-time usage analytics page in a product by issuing Propel metric queries parameterized by customer, date range, and dimension breakdowns
- • Define reusable Metric resources (via API or UI) and have application agents query them dynamically to answer ad-hoc data questions on behalf of users
- • Implement multi-tenant data isolation by using Propel's Policy layer to ensure each customer's API token can only query their own data
Not For
- • General-purpose data transformation or ETL pipelines — Propel is a query and serving layer, not a transformation engine
- • Replacing a full data warehouse for internal BI tooling — Propel is optimized for embedded customer-facing analytics
- • Machine learning training or batch data export at petabyte scale
Interface
Authentication
Uses OAuth 2.0 client credentials flow to obtain bearer tokens. Application credentials (client ID + secret) are exchanged for short-lived access tokens. Per-tenant data isolation is enforced via Policies attached to access tokens, enabling customer-scoped tokens for embedded use.
Pricing
Pricing is based on queries per month and GB of data stored. Developer plan is free with no credit card required.
Agent Metadata
Known Gotchas
- ⚠ Access tokens expire and must be refreshed — agents that cache tokens without checking expiry will receive 401 errors mid-session
- ⚠ Policy filters for multi-tenant isolation must be explicitly attached to the token at generation time; forgetting a policy allows cross-tenant data access
- ⚠ GraphQL introspection is available but the Metric schema is dynamic — metric names and dimensions must be fetched at runtime before issuing queries
- ⚠ Data ingestion latency from push to queryability is typically a few seconds but can be higher under load — agents querying immediately after ingestion may see stale counts
- ⚠ Booster (acceleration) caches must be explicitly configured per Metric; without a Booster, high-cardinality queries over large datasets will be slower
Alternatives
Full Evaluation Report
Detailed scoring breakdown, competitive positioning, security analysis, and improvement recommendations for Propel.
Scores are editorial opinions as of 2026-03-06.