Your Guide to Creating a Warehouse-First Data Analytics Stack

This page summarizes the projects mentioned and recommended in the original post on dev.to

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  • fusioncharts-dist

    FusionCharts JavaScript Charting library. Over 95+ charts and 1,400+ maps to choose from, with integrations available for all popular JavaScript frameworks & back-end programming languages.

  • FusionCharts is a popular JavaScript-based visualization tool. One feature contributing to FusionCharts' popularity is that instead of starting each new visualization from scratch, you can use various "live" example templates by simply putting in your datasets.

  • rudderstack-docs

    Documentation repository for RudderStack - the Customer Data Platform for Developers.

  • RudderStack can be thought of as an open-source combination of Segment + Fivetran + Hightouch. It's an all-in-one customer data pipeline. It can capture event data from your digital products and send it to your data warehouse and other tools with its Event Stream feature. It uses the Cloud Extract feature to aggregate and correlate non-event data with event data in the data warehouse. And finally, to get data out of the data warehouse, it has a reverse ELT feature known as Warehouse Actions. Also, its source code is publicly available on GitHub, so you can choose to self-host or use RudderStack Cloud for a fee (but you can get started for free).

  • SurveyJS

    Open-Source JSON Form Builder to Create Dynamic Forms Right in Your App. With SurveyJS form UI libraries, you can build and style forms in a fully-integrated drag & drop form builder, render them in your JS app, and store form submission data in any backend, inc. PHP, ASP.NET Core, and Node.js.

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  • nodejs-bigquery

    Node.js client for Google Cloud BigQuery: A fast, economical and fully-managed enterprise data warehouse for large-scale data analytics.

  • BigQuery is a serverless, highly scalable, and cost-effective multi-cloud data warehouse built by Google Cloud. It is based on Google's internal column-based data processing technology, "Dremel", and therefore is able to handle both structured and semi-structured data. It is also a fully managed data warehouse and can automatically allocate computing and storage resources as you need them.

NOTE: The number of mentions on this list indicates mentions on common posts plus user suggested alternatives. Hence, a higher number means a more popular project.

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