Best ETL Software for Maxio

Find and compare the best ETL software for Maxio in 2024

Use the comparison tool below to compare the top ETL software for Maxio on the market. You can filter results by user reviews, pricing, features, platform, region, support options, integrations, and more.

  • 1
    Grow Reviews
    Grow is a full-stack, no-code business intelligence (BI), platform that empowers everyone within your organization to make data-driven decision. Any organization can connect to its data and discover insights by combining ETL, data warehouses, and visualization in one platform. Our unlimited-user license model allows everyone to access the answers they seek without having to wait for an analyst. Everyone can now make great decisions in real time to accelerate their growth. Plus: Unlimited Users - More than 100 Integrations - No SQL required (but still available for use) - BI Consultants Support - Simple ETL Dynamic Dashboards
  • 2
    Rivery Reviews

    Rivery

    Rivery

    $0.75 Per Credit
    Rivery’s ETL platform consolidates, transforms, and manages all of a company’s internal and external data sources in the cloud. Key Features: Pre-built Data Models: Rivery comes with an extensive library of pre-built data models that enable data teams to instantly create powerful data pipelines. Fully managed: A no-code, auto-scalable, and hassle-free platform. Rivery takes care of the back end, allowing teams to spend time on mission-critical priorities rather than maintenance. Multiple Environments: Rivery enables teams to construct and clone custom environments for specific teams or projects. Reverse ETL: Allows companies to automatically send data from cloud warehouses to business applications, marketing clouds, CPD’s, and more.
  • 3
    Airbyte Reviews

    Airbyte

    Airbyte

    $2.50 per credit
    All your ELT data pipelines, including custom ones, will be up and running in minutes. Your team can focus on innovation and insights. Unify all your data integration pipelines with one open-source ELT platform. Airbyte can meet all the connector needs of your data team, no matter how complex or large they may be. Airbyte is a data integration platform that scales to meet your high-volume or custom needs. From large databases to the long tail API sources. Airbyte offers a long list of connectors with high quality that can adapt to API and schema changes. It is possible to unify all native and custom ELT. Our connector development kit allows you to quickly edit and create new connectors from pre-built open-source ones. Transparent and scalable pricing. Finally, transparent and predictable pricing that scales with data needs. No need to worry about volume. No need to create custom systems for your internal scripts or database replication.
  • 4
    Meltano Reviews
    Meltano offers the most flexibility in deployment options. You control your data stack from beginning to end. Since years, a growing number of connectors has been in production. You can run workflows in isolated environments and execute end-to-end testing. You can also version control everything. Open source gives you the power and flexibility to create your ideal data stack. You can easily define your entire project in code and work confidently with your team. The Meltano CLI allows you to quickly create your project and make it easy to replicate data. Meltano was designed to be the most efficient way to run dbt and manage your transformations. Your entire data stack can be defined in your project. This makes it easy to deploy it to production.
  • 5
    Singer Reviews
    Singer explains how data extraction scripts called taps and data loading scripts called targets should communicate. This allows them to be used in any combination to move any data from any source to any destination. You can send data between web APIs, databases, files, queues, or just about any other type of data you can think of. Simple applications with pipes, called singer taps and targets, are all that's required. There are no daemons nor complicated plugins. Singer applications communicate with JSON which makes them easy to use and implement in any programming language. Singer supports JSON Schema, which allows for rich data types and rigid structures when required. Singer makes it easy for incremental extraction to be supported by Singer's state-preserving invocations.
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