Innovation without vendor lock in

Enterprise grade platform and support

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  Modular by design

  The Matatika Platform builds and deploys completely portable data projects with code or no-code through our Lab. Data projects build with Matatika are hosted in our cloud-native technology stack on your cloud or ours, and can always be hosted independently if you ever need to.
  
  A wide range of Matatika and Community plugins can be added to help with your data processing and when deployed in the Matatika Platform all scheduling, metering, logging, and data engineering needs are managed for you.

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  CLI first pipelines with Meltano

  Meltano is primarily a CLI tool designed to allow data engineers to build data pipelines from the ground up. Your Matatika workspace includes a fully managed Meltano project that is 100% portable. This puts you in complete control of your project with or without the Matatika Platform.
  
  One of the main reasons we chose to integrate with Meltano is due to the way the data pipelines are captured as code in a meltano.yml file. This data as code approach means that your data pipelines can support build and change management, which is a key part of how we orchestrate a DataOps change promotion strategy. Together with Matatika, release, recovery, and rollback of your data pipelines is a breeze.
  
  Matatika are active contributors to Meltano and will continue to invest in other technologies that help our customers’ implement advanced solutions without the complexity of building connectors and data load code.
  
  Matatika with Meltano is a powerful open source alternative to:
  – Stitch
  – Fivetran
  – Airbyte
  – Funnel
  

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  SQL-first transformations with dbt™

  dbt™ is a SQL-first transformation tool that enables analytics engineers to develop code following software engineering best practices like modularity, portability, CI/CD, and documentation. The main reason we chose to integrate with dbt is the transformations as code approach that it enables - a huge community that understands how to develop in dbt makes the choice a clear winner for our customers too. Developing transforms in code with SQL and the auto generated documentation enables enterprise-grade data pipelines in tools that data engineers instinctively understand.
  
  Version Control and CI/CD
  Use Matatika to deploy and promote changes between dev, UAT, and production environments. Git-enabled version control enables collaboration and rollback.
  
  Test and Document
  Use Matatika to develop and test every model prior to production release, and share dynamically generated documentation with all stakeholders.
  
  Develop
  Data engineers write modular data transformations in .sql or .py files – Matatika together with dbt handles the chore of dependency management.
  
  Matatika with dbt is a powerful open source alternative to:
  – Matillion
  – Alteryx
  – talend
  

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  Scaleable automation and scheduling with Spring

  Data pipelines in the Matatika Platform are defined in code, enabling analytics engineers to orchestrate multi-step tasks with schedules, retry, and alerting taken care of by the platform. Integrating with Spring enables our platform to scale micro-services to meet any load our customers throw at us.
  
  Using a proven technology like Spring in our API, persistence, tasks, and health services means we are able to provide robust services and deliver future proof technology to our customers.
  
  A powerful open source alternative to:
  – Airflow
  – Prefect
  – Dagster