What is Propel Data?
Propel Data offers a robust platform centered around serverless ClickHouse®, designed to accelerate the development and deployment of AI and analytics applications. It provides a fully managed, high-performance analytics backend, eliminating the need for users to manage clusters, DevOps, or uptime concerns. The service features instant auto-scaling, mission-critical reliability, and secure GraphQL and SQL APIs, enabling developers to serve blazing-fast queries at any scale.
The platform supports unifying batch and streaming data through built-in ingestion pipelines from various sources like Kafka, Snowflake, Amazon S3, and webhooks. It includes a semantic layer for defining metrics once and querying them anywhere, along with multi-tenant access controls for securely building analytics into SaaS applications. Propel Data also offers a suite of embeddable UI components and query APIs optimized for common data access patterns, simplifying the creation of native-looking in-product analytics experiences and custom reports.
Features
- Serverless ClickHouse®: Fully managed, auto-scaling, real-time analytics database.
- Built-in Ingestion Pipelines: Unify warehouse and streaming data from sources like Kafka, Snowflake, S3, Webhooks.
- Query APIs: Optimized APIs for common patterns like Time Series, Leaderboards, Data Grids, and Counters.
- Semantic Layer: Define metrics centrally for consistent querying across applications.
- Multi-tenant Access Controls: Securely manage data access in multi-tenant SaaS applications with row and column-level policies.
- Embeddable UI Components: Open-source React components for building dashboards and analytics interfaces.
- SQL & GraphQL Interfaces: Query data using standard SQL (via API or PostgreSQL-compatible interface) or GraphQL.
- Real-time Transformations: Use Materialized Views to clean, join, aggregate, and enrich data in real-time.
- Flexible Deployment: Connect to self-hosted ClickHouse/ClickHouse Cloud or use the fully managed serverless option.
Use Cases
- Building customer-facing analytics dashboards within SaaS products.
- Deploying low-latency data APIs for various applications.
- Creating real-time IoT and operational insight dashboards.
- Metering and reporting product usage for billing or insights.
- Tracking and analyzing LLM usage metrics.
- Enabling self-service custom reporting for end-users.
- Securely sharing data with customers via a SQL interface.
- Powering internal tools and dashboards.
FAQs
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What is data read by queries?
Data read by queries is the volume of data Propel needs to scan to answer a query. The amount depends on the size of your dataset and the complexity of your query. -
What constitutes data written?
Data written includes data ingested into Propel Data Pools, data updated or deleted in Data Pools, and data inserted by Materialized views into Data Pools. -
How is storage cost calculated?
Propel measures the amount of data stored every hour. At the end of the month, it sums all the GBs counted and multiplies them by the GB-hour price. Storage is billed per compressed data size. -
Are there volume discounts available?
Yes, capacity commitments give you volume discounts. Contact sales for more information. -
Where do you store my data?
Data is stored in the AWS us-east-2 region by default. If you have requirements to deploy in another region, contact sales.
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