Software Alternatives, Accelerators & Startups

GitHub VS Databricks

Compare GitHub VS Databricks and see what are their differences

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GitHub logo GitHub

Originally founded as a project to simplify sharing code, GitHub has grown into an application used by over a million people to store over two million code repositories, making GitHub the largest code host in the world.

Databricks logo Databricks

Databricks provides a Unified Analytics Platform that accelerates innovation by unifying data science, engineering and business.‎What is Apache Spark?
  • GitHub Landing page
    Landing page //
    2023-10-05
  • Databricks Landing page
    Landing page //
    2023-09-14

GitHub

Website
github.com
$ Details
Release Date
2008 January
Startup details
Country
United States
State
California
Founder(s)
Chris Wanstrath
Employees
500 - 999

GitHub features and specs

  • collaboration
    GitHub provides a platform for multiple developers to work on the same project concurrently, facilitating collaboration through features like pull requests, code reviews, and issues tracking.
  • integration
    GitHub integrates seamlessly with various third-party tools and services, such as CI/CD pipelines, project management tools, and many development environments, enhancing productivity and workflow efficiency.
  • version_control
    Utilizes Git for version control, allowing users to track changes, revert to previous versions if necessary, and manage different branches of development, ensuring code stability and history tracking.
  • community
    With millions of developers and a vast repository of open-source projects, GitHub fosters a robust community where users can contribute to projects, seek help, share knowledge, and collaborate broadly.
  • availability
    GitHub is a cloud-based platform, which means that projects are accessible from anywhere with an internet connection, providing flexibility and convenience to developers globally.
  • documentation
    GitHub allows for comprehensive project documentation through README files, wikis, and GitHub Pages, making it easier for users to understand project context and contribute effectively.

Possible disadvantages of GitHub

  • cost
    While GitHub offers free plans, more advanced features and private repositories come at a cost, which might be a barrier for some individuals or small teams.
  • steep_learning_curve
    For newcomers, especially those unfamiliar with Git, the learning curve can be quite steep, making it challenging to utilize all of GitHub's features effectively.
  • privacy_concerns
    Given its expansive, open nature, users must be cautious with sensitive or proprietary information. Even with private repositories, there is a latent concern over data privacy and security.
  • interface_complexity
    The user interface, while powerful, can be overwhelming and complex for beginners or those not deeply familiar with version control concepts.
  • performance_issues
    Occasionally, GitHub may experience downtime or performance issues, which can disrupt workflow and prevent access to repositories temporarily.
  • limited_storage
    GitHub imposes limitations on storage space and file size within repositories, which can be restrictive for projects requiring large datasets or binaries.

Databricks features and specs

  • Unified Data Analytics Platform
    Databricks integrates various data processing and analytics tools, offering a unified environment for data engineering, machine learning, and business analytics. This integration can streamline workflows and reduce the complexity of data management.
  • Scalability
    Databricks leverages Apache Spark and other scalable technologies to handle large datasets and high computational workloads efficiently. This makes it suitable for enterprises with significant data processing needs.
  • Collaborative Environment
    The platform offers collaborative notebooks that allow data scientists, engineers, and analysts to work together in real-time. This enhances productivity and fosters better communication within teams.
  • Performance Optimization
    Databricks includes various performance optimization features such as caching, indexing, and query optimization, which can significantly speed up data processing tasks.
  • Support for Various Data Formats
    The platform supports a wide range of data formats and sources, including structured, semi-structured, and unstructured data, making it versatile and adaptable to different use cases.
  • Integration with Cloud Providers
    Databricks is designed to work seamlessly with major cloud providers like AWS, Azure, and Google Cloud, allowing users to easily integrate it into their existing cloud infrastructure.

Possible disadvantages of Databricks

  • Cost
    Databricks can be expensive, especially for large-scale deployments or high-frequency usage. It may not be the most cost-effective solution for smaller organizations or projects with limited budgets.
  • Complexity
    While powerful, Databricks can be complex to set up and manage, requiring specialized knowledge in Apache Spark and cloud infrastructure. This might lead to a steeper learning curve for new users.
  • Dependency on Cloud Providers
    Being heavily integrated with cloud providers, Databricks might face issues like vendor lock-in, where switching providers becomes difficult or costly.
  • Limited Offline Capabilities
    Databricks is primarily designed for cloud environments, which means offline or on-premise capabilities are limited, posing challenges for organizations with strict data governance policies.
  • Resource Management
    Efficiently managing and allocating resources can be challenging in Databricks, especially in large multi-user environments. Mismanagement of resources could lead to increased costs and reduced performance.

GitHub videos

How to do coding peer reviews with Github

More videos:

Databricks videos

Introduction to Databricks

More videos:

  • Tutorial - Azure Databricks Tutorial | Data transformations at scale
  • Review - Databricks - Data Movement and Query

Category Popularity

0-100% (relative to GitHub and Databricks)
Software Development
100 100%
0% 0
Data Dashboard
0 0%
100% 100
Code Collaboration
100 100%
0% 0
Big Data Analytics
0 0%
100% 100

User comments

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Reviews

These are some of the external sources and on-site user reviews we've used to compare GitHub and Databricks

GitHub Reviews

  1. Reinhard
    · Boss at CLOUD Meister ·
    perfect 4 open Source

Best Forums for Developers to Join in 2025
GitHub Discussions is a communication forum for the community around an open source or internal project. Discussions enable fluid, open conversation in a public forum. Discussions are transparent and accessible, but they are not related to code.
Source: www.notchup.com
The Top 10 GitHub Alternatives
However, like any (human) product, the platform has its limits, downsides, and critics. GitHub has been barred by certain governments, and even if that isn’t exactly the company’s fault, the users are the ones limited from pushing their code. Another criticism concerns the price tag: some users have pointed out that GitHub’s pricing model is too inflexible. Moreover, some...
Top 10 Developer Communities You Should Explore
GitHub also has an extensive API that allows it to integrate workflows seamlessly. Continuous integration, code review tools, and project management features make GitHub an essential tool for any developer, and the community aspect adds a layer of connectivity that enriches the overall experience.
Source: www.qodo.ai
Top 7 GitHub Alternatives You Should Know (2024)
FAQs: Are there any cloud source repositories similar to GitHub?Is there a free alternative to GitHub?
Source: snappify.com
Best GitHub Alternatives for Developers in 2023
We may earn from vendors via affiliate links or sponsorships. This might affect product placement on our site, but not the content of our reviews. See our Terms of Use for details. Looking for an alternative to GitHub? Check out our in-depth list of the best GitHub competitors, covering their features, pricing, pros, cons, and more.

Databricks Reviews

Jupyter Notebook & 10 Alternatives: Data Notebook Review [2023]
Databricks notebooks are a popular tool for developing code and presenting findings in data science and machine learning. Databricks Notebooks support real-time multilingual coauthoring, automatic versioning, and built-in data visualizations.
Source: lakefs.io
7 best Colab alternatives in 2023
Databricks is a platform built around Apache Spark, an open-source, distributed computing system. The Databricks Community Edition offers a collaborative workspace where users can create Jupyter notebooks. Although it doesn't offer free GPU resources, it's an excellent tool for distributed data processing and big data analytics.
Source: deepnote.com
Top 5 Cloud Data Warehouses in 2023
Jan 11, 2023 The 5 best cloud data warehouse solutions in 2023Google BigQuerySource: https://cloud.google.com/bigqueryBest for:Top features:Pros:Cons:Pricing:SnowflakeBest for:Top features:Pros:Cons:Pricing:Amazon RedshiftSource: https://aws.amazon.com/redshift/Best for:Top features:Pros:Cons:Pricing:FireboltSource: https://www.firebolt.io/Best for:Top...
Top 10 AWS ETL Tools and How to Choose the Best One | Visual Flow
Databricks is a simple, fast, and collaborative analytics platform based on Apache Spark with ETL capabilities. It accelerates innovation by bringing together data science and data science businesses. It is a fully managed open-source version of Apache Spark analytics with optimized connectors to storage platforms for the fastest data access.
Source: visual-flow.com
Top Big Data Tools For 2021
Now Azure Databricks achieves 50 times better performance thanks to a highly optimized version of Spark. Databricks also enables real-time co-authoring and automates versioning. Besides, it features runtimes optimized for machine learning that include many popular libraries, such as PyTorch, TensorFlow, Keras, etc.

Social recommendations and mentions

Based on our record, GitHub seems to be a lot more popular than Databricks. While we know about 2256 links to GitHub, we've tracked only 18 mentions of Databricks. We are tracking product recommendations and mentions on various public social media platforms and blogs. They can help you identify which product is more popular and what people think of it.

GitHub mentions (2256)

  • Unveiling PHP License 3.0: A Comprehensive Summary, Exploration and Review
    We invite you to join the discussion and explore further on platforms like GitHub and Twitter, where the conversation around open source funding and licensing continues to evolve. - Source: dev.to / about 17 hours ago
  • Next.js Setup Guide for Developers
    Git remote add origin https://github.com/username/next-hello-world.git. - Source: dev.to / 1 day ago
  • GitHub Projects My Way
    I am using GitHub for both personal and work projects. In the past, I used BitBucket, and at some point I considered using GitLab, too. However, the popularity of GitHub and its ecosystem made it hard to ignore. I even use GitHub to follow trends in my profession. - Source: dev.to / 4 days ago
  • Building Your First AI Agent: A Practical Guide for Developers
    Def search_github_issues(repo, query, state="open"): # Your GitHub API code here return {"issues": [{"title": "Example issue", "number": 42, "url": "https://github.com/..."}]}. - Source: dev.to / 5 days ago
  • India Open Source Development: Harnessing Collaborative Innovation for Global Impact
    This post provides a comprehensive exploration of India’s dynamic open source development ecosystem. It delves into historical context, core concepts, community building, practical applications, challenges, and future innovations. We discuss how talented developers, vibrant communities, and supportive government initiatives converge to power open source growth in India. The article also integrates additional... - Source: dev.to / 10 days ago
View more

Databricks mentions (18)

  • Platform Engineering Abstraction: How to Scale IaC for Enterprise
    Vendors like Confluent, Snowflake, Databricks, and dbt are improving the developer experience with more automation and integrations, but they often operate independently. This fragmentation makes standardizing multi-directional integrations across identity and access management, data governance, security, and cost control even more challenging. Developing a standardized, secure, and scalable solution for... - Source: dev.to / 7 months ago
  • dolly-v2-12b
    Dolly-v2-12bis a 12 billion parameter causal language model created by Databricks that is derived from EleutherAI’s Pythia-12b and fine-tuned on a ~15K record instruction corpus generated by Databricks employees and released under a permissive license (CC-BY-SA). Source: about 2 years ago
  • Clickstream data analysis with Databricks and Redpanda
    Global organizations need a way to process the massive amounts of data they produce for real-time decision making. They often utilize event-streaming tools like Redpanda with stream-processing tools like Databricks for this purpose. - Source: dev.to / over 2 years ago
  • DeWitt Clause, or Can You Benchmark %DATABASE% and Get Away With It
    Databricks, a data lakehouse company founded by the creators of Apache Spark, published a blog post claiming that it set a new data warehousing performance record in 100 TB TPC-DS benchmark. It was also mentioned that Databricks was 2.7x faster and 12x better in terms of price performance compared to Snowflake. - Source: dev.to / almost 3 years ago
  • A Quick Start to Databricks on AWS
    Go to Databricks and click the Try Databricks button. Fill in the form and Select AWS as your desired platform afterward. - Source: dev.to / about 3 years ago
View more

What are some alternatives?

When comparing GitHub and Databricks, you can also consider the following products

GitLab - Create, review and deploy code together with GitLab open source git repo management software | GitLab

Google BigQuery - A fully managed data warehouse for large-scale data analytics.

BitBucket - Bitbucket is a free code hosting site for Mercurial and Git. Manage your development with a hosted wiki, issue tracker and source code.

Looker - Looker makes it easy for analysts to create and curate custom data experiences—so everyone in the business can explore the data that matters to them, in the context that makes it truly meaningful.

VS Code - Build and debug modern web and cloud applications, by Microsoft

Jupyter - Project Jupyter exists to develop open-source software, open-standards, and services for interactive computing across dozens of programming languages. Ready to get started? Try it in your browser Install the Notebook.