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Databricks VS Open Collective

Compare Databricks VS Open Collective and see what are their differences

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Databricks logo Databricks

Databricks provides a Unified Analytics Platform that accelerates innovation by unifying data science, engineering and business.‎What is Apache Spark?

Open Collective logo Open Collective

Recurring funding for groups.
  • Databricks Landing page
    Landing page //
    2023-09-14
  • Open Collective Landing page
    Landing page //
    2023-04-25

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.

Open Collective features and specs

  • Transparency
    Open Collective offers transparent accounting and financial reporting, allowing everyone to see how funds are being used.
  • Community Engagement
    It allows communities to come together and support projects they care about with funding, facilitating strong community involvement.
  • Easy Fundraising
    The platform simplifies the process of raising funds for open source projects, non-profits, and other community-driven initiatives.
  • Global Reach
    Open Collective supports contributions from around the world, which can significantly expand the pool of potential donors and supporters.
  • Managed Fiscal Hosting
    It provides fiscal hosting services that handle various financial and administrative tasks, reducing the workload for project maintainers.

Possible disadvantages of Open Collective

  • Fees
    Open Collective charges fees for its services, which can be a downside for projects with limited budgets.
  • Complexity for Small Projects
    For very small projects or initiatives, the platform might be overly complex and offer more features than needed.
  • Dependence on Platform
    Relying solely on Open Collective for funding and financial management might create dependency, limiting flexibility to switch strategies.
  • Geographical Limitations
    While it has global reach, there may be certain countries where donors or users face restrictions or limitations in using the platform.
  • Learning Curve
    New users might find the platform's features and options overwhelming at the start, requiring time to learn and navigate effectively.

Databricks videos

+ Add

Introduction to Databricks

More videos:

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

Open Collective videos

+ Add

What is Open Collective?

Category Popularity

0-100% (relative to Databricks and Open Collective)

Databricks

Open Collective

Data Dashboard
100 100%
Data Dashboard
0% 0
Crowdfunding
0 0%
Crowdfunding
100% 100
Big Data Analytics
100 100%
Big Data Analytics
0% 0
Fundraising And Donation Management
0 0%
Fundraising And Donation Management
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 Databricks and Open Collective

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...
Source: www.shipyardapp.com
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.
Source: blog.bismart.com

Open Collective Reviews

We have no reviews of Open Collective yet.
Be the first one to post

Social recommendations and mentions

Based on our record, Open Collective should be more popular than Databricks. It has been mentiond 159 times since March 2021. 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.

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 / 8 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 / almost 3 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

Open Collective mentions (159)

  • Funding in Open Source: A Conversation with Chad Whitacre
    Chad has been leading the Open Source Pledge, a simple framework to get companies to fund the projects they rely on. The idea is straightforward: for every developer your company employs, allocate $2,000 per year to open source. Distribute those funds however you want—GitHub Sponsors, Open Collective, Thanks.dev, direct payments, etc. The only other ask is to publish a blog post showing what you did. - Source: dev.to / 18 days ago
  • None of the top 10 projects in GitHub is actually a software project 🤯
    We see some projects that can financially survive (via sponsor or external infrastructure such as open collective or patreon), favoring the long-term sustainability. Thus, we keep our stand on promoting a transparent governance model to state where the investment will be managed and who can benefit from it, especially when knowing that non-technical users have an increasing key role in these communities. - Source: dev.to / 18 days ago
  • Sustainable Funding for Open Source: Navigating Challenges and Emerging Innovations
    Leverage multiple platforms: Utilize GitHub Sponsors along with OpenCollective to broaden funding sources. - Source: dev.to / 18 days ago
  • Exploring Open Source Project Sponsorship Opportunities: Enhancing Innovation with Blockchain and NFTs
    Traditionally, open source projects were sustained by volunteer contributions and modest donations. However, as digital infrastructure came to rely on open source software, the need for reliable, scalable funding became evident. Enter corporate sponsorship—a model where companies invest in open source initiatives to secure their technology stacks, attract top talent, and foster innovation. This has spurred the... - Source: dev.to / 20 days ago
  • Innovative Strategies for Open Source Project Funding: A Comprehensive Guide
    Abstract: This post explores various open source project funding strategies and examines their evolution, core concepts, applications, challenges, and future trends. We discuss methods such as sponsorship and donations, crowdfunding, dual licensing, paid services, foundations and grants, and the freemium model. Through real-world examples and a technical yet accessible approach, this guide offers insight into... - Source: dev.to / 20 days ago
View more

What are some alternatives?

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

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

GitHub Sponsors - Get paid to build what you love on GitHub

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.

Liberapay - Liberapay is a recurrent donations platform.

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.

Patreon - Patreon enables fans to give ongoing support to their favorite creators.

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