evidence

Evidence enables you to deliver a polished business intelligence system using SQL and markdown (by evidence-dev)

Evidence Alternatives

Similar projects and alternatives to evidence

  • metriql

    evidence VS metriql

    The metrics layer for your data. Join us at https://metriql.com/slack

  • kuwala

    evidence VS kuwala

    Kuwala is the no-code data platform for BI analysts and engineers enabling you to build powerful analytics workflows. We are set out to bring state-of-the-art data engineering tools you love, such as Airbyte, dbt, or Great Expectations together in one intuitive interface built with React Flow. In addition we provide third-party data into data science models and products with a focus on geospatial data. Currently, the following data connectors are available worldwide: a) High-resolution demograp

  • Appwrite

    Appwrite - The Open Source Firebase alternative introduces iOS support. Appwrite is an open source backend server that helps you build native iOS applications much faster with realtime APIs for authentication, databases, files storage, cloud functions and much more!

  • Trino

    evidence VS Trino

    Official repository of Trino, the distributed SQL query engine for big data, formerly known as PrestoSQL (https://trino.io)

  • rmarkdown

    Dynamic Documents for R

  • re_data

    evidence VS re_data

    re_data - fix data issues before your users & CEO would discover them 😊

  • streamlit

    evidence VS streamlit

    Streamlit — The fastest way to build data apps in Python

  • lightdash

    evidence VS lightdash

    Open source BI for teams that move fast ⚡️

  • SonarLint

    Clean code begins in your IDE with SonarLint. Up your coding game and discover issues early. SonarLint is a free plugin that helps you find & fix bugs and security issues from the moment you start writing code. Install from your favorite IDE marketplace today.

  • superset

    evidence VS superset

    Apache Superset is a Data Visualization and Data Exploration Platform

  • fal

    evidence VS fal

    do more with dbt. fal helps you run Python alongside dbt, so you can send Slack alerts, detect anomalies and build machine learning models.

  • tellery

    evidence VS tellery

    Tellery lets you build metrics using SQL and bring them to your team. As easy as using a document. As powerful as a data modeling tool.

  • hackernews-insight

    Hackernews Insight using TiDB Cloud

NOTE: The number of mentions on this list indicates mentions on common posts plus user suggested alternatives. Hence, a higher number means a better evidence alternative or higher similarity.

evidence reviews and mentions

Posts with mentions or reviews of evidence. We have used some of these posts to build our list of alternatives and similar projects. The last one was on 2022-12-23.
  • Show HN: Hacker News Insight
    2 projects | news.ycombinator.com | 23 Dec 2022
    The home page of the Hacker News Insight site gives a bit of background about the stack: looks like TiDB Cloud database (https://www.pingcap.com/tidb-cloud/) and Evidence front-end (https://evidence.dev)
  • What are the 5 hottest dbt Repositories one should star on GitHub 2022?
    4 projects | news.ycombinator.com | 15 Jun 2022
    What are the 5 hottest dbt Repositories one should star on Github 2022?

    dbt is a software framework that sits in the middle of the ELT process. It represents the transformative layer after loading data from an original source. Dbt combines SQL with software engineering principles.

    Here are my top5!

    - Lightdash (https://github.com/lightdash/lightdash): Lightdash converts dbt models and makes it possible to define and easily visualize additional metrics via a visual interface.

    - ⏎ re_data (https://github.com/re-data/re-data): Re-Data is an abstraction layer that helps users monitor dbt projects and their underlying data. For example, you get alerts when a test failed or a data anomaly occurs in a dbt project.

    - evidence (https://github.com/evidence-dev/evidence): Evidence is another tool for lightweight BI reporting. With Evidence, you can build simple reports in "medium style" using SQL queries and Markdown.

    - Kuwala (https://github.com/kuwala-io/kuwala): With Kuwala, a BI analyst can intuitively build advanced data workflows using a drag-drop interface on top of the modern data stack without coding. Behind the Scenes, the dbt models are generated so that a more experienced engineer can customize the pipelines at any time.

    - fal ai (https://github.com/fal-ai/fal): Fal helps to run Python scripts directly from the dbt project. For example, you can load dbt models directly into the Python context which helps to apply Data Science libraries like SKlearn and Prophet in the dbt models.

  • What are the hottest dbt Repositories you should star on Github 2022? - Here are mine.
    5 projects | dev.to | 8 Jun 2022
    Evidence ( https://github.com/evidence-dev/evidence ) Evidence is another tool for lightweight BI reporting. With Evidence you can build simple reports in “medium style” using SQL queries and Markdown. It is reminiscent of Jupyter Notebooks except that it is based on SQL instead of Python. You can also initiate SQL queries from the reports you create. I haven’t used the tool myself yet but it seems to be ideal for quick prototyped metrics in a report.
  • What are your hottest dbt repositories in 2022 so far? Here are mine!
    5 projects | reddit.com/r/dataengineering | 7 Jun 2022
    - 📗 evidence: Evidence is another tool for lightweight BI reporting. With Evidence you can build simple reports in "medium style" using SQL queries and Markdown.
  • Launch HN: Evidence (YC S21) – Web framework for data analysts
    4 projects | news.ycombinator.com | 25 Aug 2021
    Hi HN!

    We’re Adam and Sean from Evidence (https://evidence.dev). We’re building a static site generator for data analysts.

    It's like Jekyll or Hugo for SQL analysts.

    In Evidence, pages are markdown documents. When you write SQL inside that markdown, the SQL runs against your database (we support BigQuery, Snowflake, and Postgres - with more to come). You can reference the results of those queries using a simple templating syntax, which you can use to inline query results into text or to generate report sections from a query. Evidence also includes a component library that lets you do things like add charts and graphs (driven by your queries) by writing declarative tags like:

    How is it different? Most BI tools use a no-code drag-and-drop interface. Analysts click around to build their queries, set up their charts etc. and then they drag them into place onto a dashboard. To stick with the analogy, if Evidence is Hugo, most BI tools are Squarespace. BI tools are built that way because they assume that data analysts are fundamentally non-technical. In our experience, that assumption is no longer correct. Data analysts increasingly want tools that let them adopt software engineering practices like version control, testing, and abstraction.

    When everything is under version control, you are less likely to ship an incorrect report. When you can write a for loop, you can show sections for each region, product-line etc., instead of asking your users to engage with a filter interface. When you can abstract a piece of analysis into a reusable component, you don’t have to maintain the same content in multiple places. Basically, we’re providing the fundamentals of programming in a way that analysts can easily make use of.

    Reporting tools have been around since COBOL, and have gone through many iterations as tech and markets have evolved. Our view is that it’s time for the next major iteration. We worked together for five years building the data science group at a private equity firm in Canada. We set up ‘the modern data stack’ (Fivetran, dbt, BigQuery etc.) at many of the firm’s portfolio companies and we were in the room during a lot of key corporate decisions.

    In our experience, the BI layer is the weakest part of the modern data stack. The BI layer has a poor developer experience, and decision makers don’t really like the outputs they get. It turns out, these two issues are closely related. The drag and drop experience is so slow and low-leverage that the only way to get all the content on the page is to push a lot of cognitive load onto the end user: global filters, drill down modals, grids of charts without context. Like most users, business people hate that shit. And because the production process isn’t in code, the outputs are hard to version control and test—so dashboards break, results are internally inconsistent, and so on, in just the way that software would suck if you didn’t version control and test it.

    As early adopters of the modern data stack, we saw the value in treating analytics more like software development, but we were consistently disappointed with the workflow and the quality of the outputs our team could deliver using BI tools and notebook products. Graphics teams that we admire at newspapers like the New York Times don’t use BI tools or Jupyter notebooks to present their work. They code their data products by hand, and the results are dramatically better than what you see in a typical BI deployment. That’s too much of an engineering lift for most data teams, but with a framework designed for their needs and their range of expertise, we think data teams could build products that come much closer to those high standards.

    Evidence is built on Svelte and Svelte Kit. This is the JS framework that the NYT has used to build some of their more recent data products, like their Covid risk maps. Sean and I fell in love with Svelte, and we owe a huge debt to that project. In this early stage,Evidence is really just a set of convenience features wrapped around SvelteKit to make it accessible to data analysts (the markdown preprocessor, db connections, chart library). The core framework will always be open source, and eventually we plan to launch a paid cloud version of our product, including hosting, granular access control, and other features that enterprises might pay for.

    We would love to hear your thoughts, questions, concerns, or ideas about what we’re building - or about your experiences with business intelligence in general. We appreciate all feedback and suggestions!

    4 projects | news.ycombinator.com | 25 Aug 2021
  • What is your preferred workflow for working with documents and code at the same time?
    2 projects | reddit.com/r/datascience | 2 Jun 2021
    I have an open source SQL in markdown tool called evidence that I released yesterday (!). It's in alpha, and it's aimed at BI and reporting use cases, but but you might find it cool.
  • Looking for Feedback: Open Source SQL-in-Markdown Reporting tool
    2 projects | reddit.com/r/SQL | 1 Jun 2021
    I think that would definitely be possible - the dev/build environment is node. You can see how our BigQuery connector is implemented here: https://github.com/evidence-dev/evidence/blob/main/packages/db-connectors/index.js
  • A note from our sponsor - Appwrite
    appwrite.io | 31 Jan 2023
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Stats

Basic evidence repo stats
13
945
8.9
6 days ago
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