Software Alternatives & Reviews

Databricks VS Apache Airflow

Compare Databricks VS Apache Airflow and see what are their differences

Databricks

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

Apache Airflow

Airflow is a platform to programmaticaly author, schedule and monitor data pipelines.
  • Databricks Landing page
    Landing page //
    2023-09-14
  • Apache Airflow Landing page
    Landing page //
    2023-06-17

Databricks

Categories
  • Data Science
  • Data Dashboard
  • Database Tools
  • Big Data Analytics
Website databricks.com  
Pricing URL Official Databricks Pricing  
Details $

Apache Airflow

Categories
  • Workflow
  • Workflow Automation
  • Data Pipelines
  • ETL
  • Automation
Website airflow.apache.org  
Pricing URL-
Details $

Databricks videos

Introduction to Databricks

More videos:

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

Apache Airflow videos

Airflow Tutorial for Beginners - Full Course in 2 Hours 2022

Category Popularity

0-100% (relative to Databricks and Apache Airflow)
Data Dashboard
100 100%
0% 0
Workflow Automation
0 0%
100% 100
Database Tools
100 100%
0% 0
Automation
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 Databricks and Apache Airflow

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.

Apache Airflow Reviews

A List of The 16 Best ETL Tools And Why To Choose Them
Apache Airflow is an open-source platform to programmatically author, schedule, and monitor workflows. The platform features a web-based user interface and a command-line interface for managing and triggering workflows.
15 Best ETL Tools in 2022 (A Complete Updated List)
Apache Airflow programmatically creates, schedules and monitors workflows. It can also modify the scheduler to run the jobs as and when required.
Python & ETL 2020: A List and Comparison of the Top Python ETL Tools
When does Apache Airflow make sense? If you're performing long ETL jobs or your ETL has multiple steps, Airflow will let you restart from any point during the ETL process. That being said, Apache Airflows IS NOT a library, so it has to be deployed and may make less sense on small ETL jobs.
Source: www.xplenty.com
Comparison of Python pipeline packages: Airflow, Luigi, Gokart, Metaflow, Kedro, PipelineX
Not designed to pass data between dependent tasks without using a database. There is no good way to pass unstructured data (e.g. image, video, pickle, etc.) between dependent tasks in Airflow.
Source: medium.com

Social recommendations and mentions

Based on our record, Apache Airflow should be more popular than Databricks. It has been mentiond 65 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 (17)

  • 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: 11 months 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 1 year 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 / over 1 year 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 / almost 2 years ago
  • data science workspace/notebook solution thoughts?
    I am considering Hex, Deepnote, and possibly Databricks. Does anyone have any experience using the first 2 (i have worked with Databricks in the past) and have thoughts they can share? The company isn't doing any fancy data science so far so I mostly want it for deep product analytics which I can turn into reports that are easily shareable across the org. That being said, I do want to get into statistical... Source: almost 2 years ago
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Apache Airflow mentions (65)

  • The 2024 Web Hosting Report
    For the third, examples here might be analytics plugins in specialized databases like Clickhouse, data-transformations in places like your ETL pipeline using Airflow or Fivetran, or special integrations in your authentication workflow with Auth0 hooks and rules. - Source: dev.to / 13 days ago
  • Best ETL Tools And Why To Choose
    Apache Airflow is an open-source platform to programmatically author, schedule, and monitor workflows. The platform features a web-based user interface and a command-line interface for managing and triggering workflows. Source: 4 months ago
  • Simplifying Data Transformation in Redshift: An Approach with DBT and Airflow
    Airflow is the most widely used and well-known tool for orchestrating data workflows. It allows for efficient pipeline construction, scheduling, and monitoring. - Source: dev.to / 4 months ago
  • Share Your favorite python related software!
    AIRFLOW This is more of a library in my opinion, but Airflow has become an essential tool for scheduling in my work. All our ML training pipelines are ordered and scheduled with Airflow and it works seamlessly. The dashboard provided is also fantastic! Source: 5 months ago
  • Ask HN: What is the correct way to deal with pipelines?
    I agree there are many options in this space. Two others to consider: - https://airflow.apache.org/ - https://github.com/spotify/luigi There are also many Kubernetes based options out there. For the specific use case you specified, you might even consider a plain old Makefile and incrond if you expect these all to run on a single host and be triggered by a new file... - Source: Hacker News / 5 months ago
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What are some alternatives?

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

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

ifttt - IFTTT puts the internet to work for you. Create simple connections between the products you use every day.

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.

Microsoft Power Automate - Microsoft Power Automate is an automation platform that integrates DPA, RPA, and process mining. It lets you automate your organization at scale using low-code and AI.

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.

Make.com - Tool for workflow automation (Former Integromat)