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Hadoop VS Azure Databricks

Compare Hadoop VS Azure Databricks and see what are their differences

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Contents:
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  2. » Videos
  3. » Reviews
  4. » Alternatives

Hadoop logo Hadoop

Open-source software for reliable, scalable, distributed computing

Azure Databricks logo Azure Databricks

Azure Databricks is a fast, easy, and collaborative Apache Spark-based big data analytics service designed for data science and data engineering.
  • Hadoop Landing page
    Landing page //
    2021-09-17
  • Azure Databricks Landing page
    Landing page //
    2023-04-02

Hadoop features and specs

  • Scalability
    Hadoop can easily scale from a single server to thousands of machines, each offering local computation and storage.
  • Cost-Effective
    It utilizes a distributed infrastructure, allowing you to use low-cost commodity hardware to store and process large datasets.
  • Fault Tolerance
    Hadoop automatically maintains multiple copies of all data and can automatically recover data on failure of nodes, ensuring high availability.
  • Flexibility
    It can process a wide variety of structured and unstructured data, including logs, images, audio, video, and more.
  • Parallel Processing
    Hadoop's MapReduce framework enables the parallel processing of large datasets across a distributed cluster.
  • Community Support
    As an Apache project, Hadoop has robust community support and a vast ecosystem of related tools and extensions.

Possible disadvantages of Hadoop

  • Complexity
    Setting up, maintaining, and tuning a Hadoop cluster can be complex and often requires specialized knowledge.
  • Overhead
    The MapReduce model can introduce additional overhead, particularly for tasks that require low-latency processing.
  • Security
    While improvements have been made, Hadoop's security model is considered less mature compared to some other data processing systems.
  • Hardware Requirements
    Though it can run on commodity hardware, Hadoop can still require significant computational and storage resources for larger datasets.
  • Lack of Real-Time Processing
    Hadoop is mainly designed for batch processing and is not well-suited for real-time data analytics, which can be a limitation for certain applications.
  • Data Integrity
    Distributed systems face challenges in maintaining data integrity and consistency, and Hadoop is no exception.

Azure Databricks features and specs

  • Scalability
    Azure Databricks enables easy scaling of workloads up or down, allowing users to handle large volumes of data and perform distributed processing efficiently.
  • Integration
    Seamlessly integrates with other Azure services, such as Azure Data Lake Storage and Azure SQL Data Warehouse, facilitating a streamlined data pipeline.
  • Collaboration
    Offers collaborative features like notebooks that allow multiple users to work together easily on data analytics projects.
  • Performance Optimization
    Built on top of Apache Spark, Azure Databricks provides high performance and optimized execution for data engineering and machine learning tasks.
  • Managed Service
    As a fully managed service, it handles infrastructure provisioning and maintenance, enabling users to focus on data insights rather than backend management.

Possible disadvantages of Azure Databricks

  • Cost
    Azure Databricks can be expensive, particularly for large-scale and long-running workloads, which may be a concern for budget-conscious organizations.
  • Complexity
    Despite its capabilities, Azure Databricks may have a steep learning curve, especially for users not familiar with Apache Spark.
  • Vendor Lock-in
    Leveraging Azure-specific services can lead to vendor lock-in, making it challenging to migrate workloads and data to other cloud platforms.
  • Limited Offline Capabilities
    As a cloud-native service, it requires an active internet connection and might not suit scenarios that require offline processing.
  • Compliance Concerns
    Due to Azure Databricks' integration with Azure, users need to carefully manage compliance and data governance, which might be complex in multi-regional deployments.

Hadoop videos

+ Add

What is Big Data and Hadoop?

More videos:

  • Review - Product Ratings on Customer Reviews Using HADOOP.
  • Tutorial - Hadoop Tutorial For Beginners | Hadoop Ecosystem Explained in 20 min! - Frank Kane

Azure Databricks videos

+ Add

Azure Databricks is Easier Than You Think

More videos:

  • Review - Ingest, prepare & transform using Azure Databricks & Data Factory | Azure Friday
  • Review - Azure Databricks - What's new! | DB102

Category Popularity

0-100% (relative to Hadoop and Azure Databricks)

Hadoop

Azure Databricks

Databases
100 100%
Databases
0% 0
Technical Computing
0 0%
Technical Computing
100% 100
Big Data
100 100%
Big Data
0% 0
Office & Productivity
0 0%
Office & Productivity
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 Hadoop and Azure Databricks

Hadoop Reviews

A List of The 16 Best ETL Tools And Why To Choose Them
Companies considering Hadoop should be aware of its costs. A significant portion of the cost of implementing Hadoop comes from the computing power required for processing and the expertise needed to maintain Hadoop ETL, rather than the tools or storage themselves.
Source: www.datacamp.com
16 Top Big Data Analytics Tools You Should Know About
Hadoop is an Apache open-source framework. Written in Java, Hadoop is an ecosystem of components that are primarily used to store, process, and analyze big data. The USP of Hadoop is it enables multiple types of analytic workloads to run on the same data, at the same time, and on a massive scale on industry-standard hardware.
Source: www.analytixlabs.co.in
5 Best-Performing Tools that Build Real-Time Data Pipeline
Hadoop is an open-source framework that allows to store and process big data in a distributed environment across clusters of computers using simple programming models. It is designed to scale up from single servers to thousands of machines, each offering local computation and storage. Rather than relying on hardware to deliver high-availability, the library itself is...
Source: www.analyticsinsight.net

Azure Databricks Reviews

10 Best Big Data Analytics Tools For Reporting In 2022
Azure Databricks is a data analytics tool optimized for Microsoft’s Azure cloud services solution. It provides three development environments for data-intensive apps, namely Databricks SQL, Databricks Machine Learning, and Databricks Data Science & Engineering.The platform supports languages including Python, Java, R, Scala, and SQL, plus data science frameworks and...
Source: theqalead.com

Social recommendations and mentions

Based on our record, Hadoop seems to be a lot more popular than Azure Databricks. While we know about 25 links to Hadoop, we've tracked only 2 mentions of Azure 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.

Hadoop mentions (25)

  • Apache Hadoop: Open Source Business Model, Funding, and Community
    This post provides an in‐depth look at Apache Hadoop, a transformative distributed computing framework built on an open source business model. We explore its history, innovative open funding strategies, the influence of the Apache License 2.0, and the vibrant community that drives its continuous evolution. Additionally, we examine practical use cases, upcoming challenges in scaling big data processing, and future... - Source: dev.to / 1 day ago
  • What is Apache Kafka? The Open Source Business Model, Funding, and Community
    Modular Integration: Thanks to its modular approach, Kafka integrates seamlessly with other systems including container orchestration platforms like Kubernetes and third-party tools such as Apache Hadoop. - Source: dev.to / 1 day ago
  • India Open Source Development: Harnessing Collaborative Innovation for Global Impact
    Over the years, Indian developers have played increasingly vital roles in many international projects. From contributions to frameworks such as Kubernetes and Apache Hadoop to the emergence of homegrown platforms like OpenStack India, India has steadily carved out a global reputation as a powerhouse of open source talent. - Source: dev.to / 8 days ago
  • Unveiling the Apache License 2.0: A Deep Dive into Open Source Freedom
    One of the key attributes of Apache License 2.0 is its flexible nature. Permitting use in both proprietary and open source environments, it has become the go-to choice for innovative projects ranging from the Apache HTTP Server to large-scale initiatives like Apache Spark and Hadoop. This flexibility is not solely legal; it is also philosophical. The license is designed to encourage transparency and maintain a... - Source: dev.to / 2 months ago
  • Apache Hadoop: Pioneering Open Source Innovation in Big Data
    Apache Hadoop is more than just software—it’s a full-fledged ecosystem built on the principles of open collaboration and decentralized governance. Born out of a need to process vast amounts of information efficiently, Hadoop uses a distributed file system and the MapReduce programming model to enable scalable, fault-tolerant computing. Central to its success is a diverse ecosystem that includes influential... - Source: dev.to / 2 months ago
View more

Azure Databricks mentions (2)

  • Top 30 Microsoft Azure Services
    In the big data space, Azure offers Azure Databricks. This is an Apache Spark big data analytics and machine learning service over a Distributed File System. The distributed cluster of nodes running analytics and AI operations in parallel allow for fast processing of large volumes of data and integration with popular machine learning libraries such as PyTorch unleash endless possibilities for custom ML. - Source: dev.to / almost 4 years ago
  • ZooKeeper-free Kafka is out. First Demo
    https://azure.microsoft.com/en-us/services/databricks. - Source: Hacker News / about 4 years ago

What are some alternatives?

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

Apache Spark - Apache Spark is an engine for big data processing, with built-in modules for streaming, SQL, machine learning and graph processing.

IBM Cloud Pak for Data - Move to cloud faster with IBM Cloud Paks running on Red Hat OpenShift – fully integrated, open, containerized and secure solutions certified by IBM.

PostgreSQL - PostgreSQL is a powerful, open source object-relational database system.

MyAnalytics - MyAnalytics, now rebranded to Microsoft Viva Insights, is a customizable suite of tools that integrates with Office 365 to drive employee engagement and increase productivity.

Apache Storm - Apache Storm is a free and open source distributed realtime computation system.

MicroStrategy - MicroStrategy is a cloud-based platform providing business intelligence, mobile intelligence and network applications.

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