How to install Steampipe and query AWS resources?

Install Steampipe via the provided shell script or package manager, then install the AWS plugin with 'steampipe plugin install aws'. Configure AWS credentials, and you can run SQL queries directly on AWS services like EC2 or S3.

Steampipe vs traditional ETL tools like Apache NiFi: which is better?

Steampipe is ideal for real-time SQL querying without data storage, while tools like Apache NiFi focus on batch ETL and data flow. Choose Steampipe for live data exploration and NiFi for complex data integration pipelines.

Can Steampipe handle authentication for multiple cloud providers at once?

Yes, Steampipe plugins allow configuring separate credentials for different services. You can query across AWS, Azure, and GCP in the same session by setting up plugin-specific configurations.

How to visualize data from Steampipe queries?

Use Steampipe with Powerpipe for dashboards, export data to CSV/JSON for BI tools, or leverage Turbot Pipes for cloud-based visualization, as mentioned in the README under integrations.

Is Steampipe suitable for production use in large teams?

Steampipe can be deployed in production with its single binary and CI/CD support, but monitor plugin updates and API limits. For team collaboration, consider Turbot Pipes for managed cloud features.

How to create a custom plugin for Steampipe?

Refer to the plugin development documentation on Steampipe.io, which provides Go templates and examples. The process involves defining tables that map API endpoints to SQL queries.

Open-Awesome

Steampipe

AGPL-3.0Gov2.4.4

Query APIs, cloud services, and code directly with SQL using a zero-ETL approach—no database required.

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7.9k stars339 forks0 contributors

What is Steampipe?

Steampipe is an open-source tool that allows developers to query APIs, cloud services, and other data sources using standard SQL without requiring a database. It provides a zero-ETL approach, enabling real-time access to live data through a unified SQL interface. The tool solves the problem of complex data pipelines by letting users directly interrogate APIs and services as if they were database tables.

Target Audience

DevOps engineers, cloud architects, and developers who need to query and analyze data from multiple APIs, cloud platforms, or services without building and maintaining ETL pipelines.

Value Proposition

Developers choose Steampipe because it eliminates the need for custom data integration code, provides real-time access to live data, and leverages familiar SQL syntax across a wide range of data sources through an extensible plugin ecosystem.

Overview

Zero-ETL, infinite possibilities. Live query APIs, code & more with SQL. No DB required.

Use Cases

Best For

Querying cloud infrastructure across AWS, Azure, and GCP in real-time
Analyzing GitHub repositories, pull requests, and issues with SQL
Monitoring Kubernetes clusters and resources via SQL queries
Building dashboards and reports from multiple API sources without ETL
Automating compliance checks across cloud services using SQL
Exploring and analyzing data from services like Hacker News or Salesforce with SQL

Not Ideal For

Historical data analysis projects requiring batch processing and data warehousing
Performance-critical applications needing direct, low-latency API calls without SQL abstraction
Teams already standardized on non-SQL query languages like GraphQL or specific API SDKs

Pros & Cons

Pros

Zero-ETL Efficiency

Eliminates the need for complex data pipelines by allowing direct SQL queries on APIs, enabling real-time access without database maintenance, as emphasized in the project description.

Extensive Plugin Support

Provides access to over 2000 tables through community-built plugins for services like AWS, GitHub, and Kubernetes, offering broad integration coverage as highlighted in the README.

High Concurrency Performance

Supports parallel querying of multiple data sources for faster insights, a key feature mentioned in the README that enhances query speed across APIs.

Flexible Deployment Options

Available as CLI, Postgres FDW, SQLite extension, and export tool, providing versatility for different environments, from local development to CI/CD pipelines.

Cons

Plugin Quality Variability

Since plugins are community-maintained, there can be inconsistencies in documentation, update frequency, and reliability, which may lead to integration issues or broken queries.

Real-Time Data Limitations

Queries live data directly without built-in caching or batch handling, making it susceptible to API rate limits and performance bottlenecks in high-volume scenarios.

SQL Overhead for Simple Use Cases

For straightforward API calls that don't require complex querying, the SQL layer adds unnecessary complexity and potential latency compared to direct API clients.

Frequently Asked Questions

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