Keboola vs Mage

Keboola is a unified AI and data platform for creating and orchestrating pipelines and operating analytics and integrations. Managed connectors bring in data, while its orchestration engine supports conditional flows, monitoring, alerts, scheduling, and triggers. Transformations can use SQL, Python, or R, though free projects are limited to Snowflake SQL and Python. Keboola lists 1,601 connectors, including Shopify, Salesforce, HubSpot, Snowflake, PostgreSQL, Google Analytics, Stripe, and BigQuery. Users can work through the web platform, REST API, CLI, or MCP server; Keboola says AI agents and assistants can operate the platform through MCP. Governance capabilities include a Data Catalog, sharing, metadata and lineage, access controls, activity monitoring, and logging. The platform runs across AWS, Azure, and GCP; enterprise customers can select a provider or region or use private cloud. Keboola states it uses AES-256 encryption at rest and TLS 1.2+ in transit, and lists SOC 2 Type II, GDPR, and HIPAA compliance capabilities. The Free plan costs nothing and includes 120 compute minutes in the first month, then 60 minutes monthly; extra compute costs $0.14 per minute.

Mage is a web platform for building and operating data workflows. Its listed functions include workflow scheduling, pipeline monitoring, data quality checks, and version control. Integrations cover Stripe, Salesforce, BigQuery, HubSpot, databases, SaaS APIs, cloud storage, files, and streams. Hybrid deployment is available. Mage has a free plan, while Starter costs $29 a month, billed monthly, plus $0.50 per CPU-hour. Starter includes one developer seat, one development environment, and 50 AI credits per month. Team costs $100 a month, billed monthly, plus $0.50 per CPU-hour; it supports up to 10 developer seats, includes one environment, and provides 250 shared AI credits per month. Mage is headquartered in Santa Clara, California, United States.