Apache Hop vs Matillion Data Productivity Cloud
Apache Hop
hop.apache.org
Matillion Data Productivity Cloud
matillion.comSide by side
| Figure | Apache Hop | Matillion Data Productivity Cloud |
|---|---|---|
| Price from | Free | — |
| Free plan | Yes | — |
| Free trial | — | Yes |
| Open source | Yes | — |
| Web | Yes | Yes |
| Windows | Yes | — |
| macOS | Yes | — |
| Linux | Yes | — |
| API | Yes | — |
| Self-hosted | Yes | — |
| Plans published | 2 | 3 |
| Spec score · Data Preparation for Analytics | 9.1 (#1) | 7.1 (#15) |
| Spec score · ETL Software | 9.0 (#3) | 7.2 (#18) |
| Spec score · Data Integration | 9.0 (#3) | 7.1 (#18) |
| Integrations | Listed integrations include PostgreSQL, MySQL, Oracle, SQL Server, Snowflake, BigQuery, Redshift, Databricks, MongoDB, Neo4j, Kafka, Cassandra, Salesforce, SAP, Parquet, Avro, S3, Azure Blob, Google Cloud Storage, REST and SFTP. | Matillion identifies Snowflake, Databricks, BigQuery, and Redshift as cloud data platforms supported by Maia Foundation. |
| Pipeline design | Users can build pipelines on a canvas, preview rows at each step, and view live data and metrics while a pipeline runs. | Users can build pipelines with a visual low-code canvas, SQL or Python components, and imported dbt models. |
| Purpose | Apache Hop is an open source platform for data integration and orchestration, with visual pipelines and workflows. | The Data Productivity Cloud builds and manages data pipelines and delivers data for AI and analytics. |
| Support | Community support is volunteer-based and free, but the project says it cannot promise response times; commercial providers offer services such as SLAs, training, and migration. | Developer includes community support, Teams includes standard support, and Scale includes standard support with Premium Support available as an option. |
Plans
Matillion Data Productivity Cloud
- DeveloperPriced on request
- TeamsPriced on request
- ScalePriced on request
In their own words
Apache Hop
Apache Hop is an open-source platform for data integration and orchestration. Its visual canvas lets users assemble pipelines, preview rows at individual steps, and watch live data and metrics during execution. A pipeline can run locally, on Hop Server, on Apache Spark, or on Flink and Dataflow through Apache Beam. Hop includes more than 250 pipeline transforms, more than 80 workflow actions, and support for over 40 database dialects. Listed connections include PostgreSQL, MySQL, Oracle, SQL Server, Snowflake, BigQuery, Kafka, Salesforce, SAP, S3, REST, and SFTP. Teams can switch environments when moving projects from development to production and keep credentials outside pipeline definitions. Apache Hop is free under the Apache License 2.0. It runs on Linux, macOS, and Windows; Hop Web works in modern browsers. Release 2.19.0 requires Java 21. Docker images and a Kubernetes Helm chart are available; Hop Web is work in progress and provided as-is.
Matillion Data Productivity Cloud
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.