Software Alternatives, Accelerators & Startups

Microsoft Azure VS Databricks

Compare Microsoft Azure VS Databricks and see what are their differences

Note: These products don't have any matching categories. If you think this is a mistake, please edit the details of one of the products and suggest appropriate categories.

Microsoft Azure logo Microsoft Azure

Windows Azure and SQL Azure enable you to build, host and scale applications in Microsoft datacenters.

Databricks logo Databricks

Databricks provides a Unified Analytics Platform that accelerates innovation by unifying data science, engineering and business.‎What is Apache Spark?
  • Microsoft Azure Landing page
    Landing page //
    2023-04-10
  • Databricks Landing page
    Landing page //
    2023-09-14

Microsoft Azure features and specs

  • Scalability
    Azure offers a highly scalable environment where you can easily adjust compute resources to match your needs.
  • Global Reach
    Azure has multiple data centers around the globe, providing extensive global coverage for applications and services.
  • Integration with Microsoft Products
    Azure integrates seamlessly with existing Microsoft software like Office 365, Active Directory, and Windows Server.
  • Compliance
    Azure adheres to a broad set of international standards and compliance certifications, including GDPR, ISO, and many others.
  • Service Offerings
    Azure provides a wide variety of services, from virtual machines to databases and AI-powered functionalities.
  • Hybrid Solutions
    Azure supports hybrid cloud configurations, allowing businesses to run some resources on-premises and some in the cloud.
  • Security
    Azure employs advanced security protocols and has multiple layers of security, including data encryption and secure access controls.

Possible disadvantages of Microsoft Azure

  • Cost Management
    The pricing structure can be complex and may lead to unexpected costs if not carefully managed.
  • Learning Curve
    New users may find Azure challenging to learn due to its extensive range of services and configurations.
  • Service Limits
    Some Azure services have limitations and quotas, which can hinder performance or scalability if reached.
  • Support Costs
    While Azure offers robust support, advanced support plans can be expensive.
  • Complexity in Hybrid Setup
    Setting up and managing a hybrid environment can be technically challenging and may require specialized skills.
  • Downtime Risks
    Although rare, Azure is not immune to outages and downtime, which can impact service availability.
  • Data Migration
    Migrating data and services into Azure can be complicated and may require significant planning and resources.

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.

Microsoft Azure videos

Building your first Azure Blockchain Workbench application

More videos:

  • Review - How does Microsoft Azure work?
  • Review - Introduction to Azure Blockchain Workbench
  • Review - Microsoft Azure Overview
  • Tutorial - What Is Azure? | Microsoft Azure Tutorial For Beginners | Microsoft Azure Training | Simplilearn
  • Review - Bots and Azure Blockchain Workbench

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 Microsoft Azure and Databricks)
Cloud Computing
100 100%
0% 0
Data Dashboard
0 0%
100% 100
Cloud Infrastructure
100 100%
0% 0
Big Data Analytics
0 0%
100% 100

User comments

Share your experience with using Microsoft Azure and Databricks. For example, how are they different and which one is better?
Log in or Post with

Reviews

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

Microsoft Azure Reviews

Top 15 MuleSoft Competitors and Alternatives
The Azure API Management platform has over a million APIs for modernizing legacy apps to adopting API-first strategies from on-premises to multi-cloud. Thousands of the world’s largest enterprises use the solution to build, secure, and scale API initiatives.
20 Best Free Website Hosting (July 2023)
New users can usually receive a free site credit at the largest cloud services like Microsoft Azure, Amazon Web Services, and Google Cloud Platform to get started. However, when these free credits expire, cloud products can be quite expensive and out of the price range of many projects.
AWS vs Azure Which is best for your career?
This course provides the key knowledge required to prepare for Exam AZ-204: Developing Solutions for Microsoft Azure. You will learn how to develop and deploy cloud applications on Azure using various Azure services.
Top 10 Best Container Software in 2022
Tool Cost/Plan Details: There is no upfront cost. Azure does not charge for cluster management. It charges only for what you use. It has Pricing for nodes model. Based on your container needs, you can get the price estimator through Container Services calculator.
Top 50 Cheapest Cloud Services Providers | Affordable Cloud Hosting
With direct competitors like AWS, Microsoft Azure has been one of the most preferred and also cheapest cloud services providers. The plan that Azure submit depends on the services a business seeks to access. Azure cloud platform includes over 200 products and cloud services to assist businesses in bringing new solutions to life—to solve today’s challenges and create the...

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, Microsoft Azure should be more popular than Databricks. It has been mentiond 66 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.

Microsoft Azure mentions (66)

  • How to Develop a Voice Chatbot
    Microsoft Azure offers a Bot Framework with built-in support for voice interactions via the Speech SDK. - Source: dev.to / 9 months ago
  • Setting Up a Windows 11 Virtual Machine with Azure on a MacOs
    The first step in creating a virtual machine is getting a Microsoft account. Once you have a Microsoft account click this link to create an Azure free trial account. Click on the "Try Azure for free" button. This takes you to the page below. - Source: dev.to / about 1 year ago
  • How To Create Windows 11 Virtual Machine in Azure
    Before you start, ensure you have an active Azure subscription, if you don't have one, Click here to create a free account. - Source: dev.to / about 1 year ago
  • The 2024 Web Hosting Report
    A VM is the original “hosting” product of the cloud era. Over the last 20 years, VM providers have come and gone, as have enterprise virtualization solutions such as VMware. Today you can do this somewhere like OVHcloud, Hetzner or DigitalOcean, which took over the “server” market from the early 2000’s. Amazon Web Services (AWS), Google Cloud Platform (GCP), and Microsoft's Azure also offer VMs, at a less... - Source: dev.to / over 1 year ago
  • Deploying flask app to Kubernetes using Minikube
    Before deploying the application with Kubernetes, you need to containerize the application using docker. This article shows how to deploy a Flask application on Ubuntu 22.04 using Minikube; a Kubernetes tool for local deployment for testing and free offering. Alternatively, you can deploy your container apps using Cloud providers such as GCP(Google Cloud), Azure(Microsoft) or AWS(Amazon). - Source: dev.to / over 1 year 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 / 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 / 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 Microsoft Azure and Databricks, you can also consider the following products

Amazon AWS - Amazon Web Services offers reliable, scalable, and inexpensive cloud computing services. Free to join, pay only for what you use.

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

DigitalOcean - Simplifying cloud hosting. Deploy an SSD cloud server in 55 seconds.

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.

Linode - We make it simple to develop, deploy, and scale cloud infrastructure at the best price-to-performance ratio in the market.

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.