Propel is a serverless analytics platform built on ClickHouse, providing secure GraphQL and SQL APIs for real-time data ingestion and analysis. It enables developers to quickly create and embed analytics features in customer-facing applications, addressing the need for fast, reliable data insights without the overhead of managing infrastructure.
Funding
$5.5M raised to dateRaised to date based on public sources. This may differ from the amount the company actually raised and is based only on what is publicly available on the internet.
Founders
Product
Problem
Building customer-facing analytics requires significant engineering effort to manage data ingestion, optimize query performance, and secure multi-tenant access. Developers often struggle to deliver real-time insights without the overhead of managing complex data infrastructure.
Solution
Propel provides a serverless ClickHouse platform with GraphQL and SQL APIs, enabling developers to quickly build and embed customer-facing analytics features. The platform offers built-in ingestion pipelines for real-time streaming data and data warehouse synchronization, along with a semantic layer for defining and querying metrics. Propel's data APIs and embeddable UI components simplify the process of creating interactive dashboards and reports, while its access control policies ensure secure, multi-tenant data access. By abstracting away the complexities of data infrastructure management, Propel allows developers to focus on delivering fast, reliable data insights to their users.
Target Audience
Propel targets developers and product teams building customer-facing applications who need to embed real-time analytics without managing complex data infrastructure.
Features
- Serverless ClickHouse with auto-scaling for high concurrency and sub-second query latencies.
- Built-in ingestion pipelines for real-time streaming data, data warehouses, and databases, compatible with Fivetran and Airbyte.
- Data APIs for common access patterns, including counter, data grid, leaderboard, metric report, time series, and top values.
- Semantic layer for defining metrics with SUM, AVG, MIN, MAX, COUNT, and COUNT_DISTINCT aggregations.
- Embeddable UI components, such as `<TimeSeries>`, `<PieChart>`, and `<Leaderboard>`, integrated with the API.
- Multi-tenant access controls with scoped API credentials and column- and row-level access policies.
- Support for SQL queries through the API, React Query Hooks, or a PostgreSQL-compatible SQL connector.