Matillion Data Productivity Cloud
matillion.com
What it is
Matillion Data Productivity Cloud builds and manages data pipelines that deliver data for AI and analytics; Matillion says it is now called Maia Foundation. Users design pipelines on a visual low-code canvas, add SQL or Python components, or import dbt models. Pre-built and custom connectors move data between systems, with Snowflake, Databricks, BigQuery, and Redshift listed as supported cloud data platforms. The platform handles batch loading and log-based change data capture, including a containerized agent for secure extraction from cloud or on-premises sources. Deployment is hybrid, with incremental loading and custom-code transformations supported. Credits are consumed by pipeline task hours and developer users beyond included allowances, while validation and sampling are not billed. The free trial provides 500 credits, full feature access, sample datasets, and a provided data warehouse without commitment. Developer targets individuals, Teams scaling businesses, and Scale large organizations. Pricing is on request. Matillion was founded in 2011 and has headquarters in Denver and Manchester.
Spec sheet
- Purpose
- The Data Productivity Cloud builds and manages data pipelines and delivers data for AI and analytics.Read 4 Oct 2026 · matillion.com
- Intended users
- Matillion describes Developer as intended for individuals, Teams for scaling businesses, and Scale for large organizations.Read 4 Oct 2026 · matillion.com
- Integrations
- Matillion identifies Snowflake, Databricks, BigQuery, and Redshift as cloud data platforms supported by Maia Foundation.Read 4 Oct 2026 · matillion.com
- Support
- Developer includes community support, Teams includes standard support, and Scale includes standard support with Premium Support available as an option.Read 4 Oct 2026 · matillion.com
- Headquarters
- Denver, Colorado, USA and Manchester, UKRead 28 Sep 2026 · matillion.com
- Founded
- 2011Read 28 Sep 2026 · matillion.com
- Company
- Matillion says it was founded in 2011 and has dual headquarters in Denver and Manchester.Read 4 Oct 2026 · matillion.com
- Batch and CDC
- The connectivity page describes batch loading and log-based change data capture pipelines, including a containerized agent for secure extraction from cloud or on-premises sources.Read 4 Oct 2026 · matillion.com
- Current name
- Matillion says the Data Productivity Cloud is now Maia Foundation.Read 4 Oct 2026 · matillion.com
- Data connectivity
- The platform offers pre-built connectors and custom connectors for moving data between systems.Read 4 Oct 2026 · matillion.com
- Pipeline design
- Users can build pipelines with a visual low-code canvas, SQL or Python components, and imported dbt models.Read 4 Oct 2026 · matillion.com
- Security and access
- The Scale plan includes custom SSO, and PrivateLink is available as an add-on.Read 4 Oct 2026 · matillion.com
- Trial allowance
- The free trial page offers 500 free credits, full feature access, sample datasets, and a provided data warehouse, without requiring a commitment.Read 4 Oct 2026 · matillion.com
- Usage limits
- Credits are consumed by pipeline task hours and developer users beyond the plan’s included users, while validation and sampling operations are not billed.Read 4 Oct 2026 · matillion.com
Plans and prices
Strong points and limits
Strong points
- Visual low-code, SQL, Python, and dbt pipeline design
- Pre-built and custom connectors
- Batch loading and log-based change capture
- Hybrid deployment with incremental loading
- 500-credit full-feature trial
Limits
- Pricing is on request
- Credits apply to task hours and extra users
- Scale features such as custom SSO require that plan
Who it suits
Developer is intended for individuals, Teams for scaling businesses, and Scale for large organizations. The platform suits teams building hybrid pipelines for analytics or AI data delivery.
Verdict
Matillion provides visual and code-based pipeline construction, broad connectivity, and batch or change-capture options. Credit-based usage and request-based pricing require planning around users and workload.
Where Specifiction places it
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