Mage review
Mage combines tested, monitored pipelines with cloud, hybrid, and self-hosted deployment.
Reviewed by iTechGuides Editors · Editorial team · Updated Oct 2026
Mage is an AI data engineering platform for data teams and developers building, scheduling, and monitoring pipelines. It supports pipeline development in Python, SQL, R, and dbt, with scheduled triggers, cross-pipeline dependencies, run history, logs, status, metrics, and monitoring dashboards. Data validations, freshness checks, schema checks, pipeline tests, and automatic recovery address operational controls, while open-source software supports self-managed deployments. Mage fits solo developers through enterprise teams that need cloud or self-hosted options.
The published plans show a free plan and a 7-day trial without a credit card. Starter costs $29 per month for one developer seat and one development environment, with managed orchestration, alerts, monitoring, and 50 AI credits monthly. Team costs $100 per month for up to 10 developer seats and one included environment, adding advanced controls, lineage, deployment workflows, and 250 shared AI credits monthly. Enterprise adds private and hybrid deployment options, custom governance and security controls, plus dedicated onboarding, support, and SLAs. The plan structure suits teams that can match environment and seat needs to tier boundaries.
Mage connects to Stripe, Salesforce, BigQuery, and HubSpot, along with databases, SaaS APIs, cloud storage, files, and streams through built-in and custom connectors. Git-based version control, autoscaling execution, resource monitoring, and deployment workflows support teams operating pipelines across cloud and self-hosted environments. Teams needing broad pipeline checks, recovery, and deployment flexibility should consider Mage; those prioritizing multiple environments at lower tiers, a larger set of named integrations, or support beyond community and documentation may prefer another platform.
Mage pros and cons
- Where it wins
- Pipeline tests, freshness and schema checks, monitoring, and recovery
- Python, SQL, R, and dbt development with Git-based workflows
- Cloud or self-hosted deployment with scheduling and dependencies
- Where it doesn't
- Starter is limited to one developer seat and one environment
- Team includes one environment, even with up to 10 developer seats
- Support channels are community and documentation
Mage fact sheet, pricing and score →
Advertiser disclosure: iTechGuides is reader-supported. Vendors can pay for top positions in our rankings and for a place on other products' pages, and we may earn a commission when you click some links. Bought places stand at the number bought; this page and our disclosure say so. Paying vendors may get a fuller, more detailed review from our editors, and that review can change their score. How we rank.
Last updated · How we research and update