Software Alternatives, Accelerators & Startups
Register | Login

Hadoop VS Azure Blob Storage

Compare Hadoop VS Azure Blob Storage and see what are their differences

Fileport
The fastest way to send files over the internet featured
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.
Contents:
  1. » Base Details
  2. » Videos
  3. » Reviews
  4. » Alternatives

Hadoop logo Hadoop

Open-source software for reliable, scalable, distributed computing

Azure Blob Storage logo Azure Blob Storage

Use Azure Blob Storage to store all kinds of files. Azure hot, cool, and archive storage is reliable cloud object storage for unstructured data
  • Hadoop Landing page
    Landing page //
    2021-09-17
  • Azure Blob Storage Landing page
    Landing page //
    2023-04-01

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 Blob Storage features and specs

  • Scalability
    Azure Blob Storage automatically scales to handle large amounts of data, enabling you to grow your storage needs without worrying about performance constraints.
  • Durability
    Azure offers high durability with multiple redundant copies of your data, ensuring that your information is safeguarded against hardware failures.
  • Cost Effectiveness
    Different tiers of storage (Hot, Cool, Archive) allow you to optimize costs based on how frequently you need to access your data.
  • Security
    Robust security features, including encryption at rest and in transit, as well as advanced threat protection, keep your data secure.
  • Integration
    Seamlessly integrates with Azure's ecosystem and other services, such as Azure Functions, Azure Data Factory, and more, for extended functionality.
  • Global Reach
    Data centers available globally ensure lower latency and compliance with local data residency requirements.
  • Automation
    Supports automation through REST APIs, SDKs, and Azure CLI, making it easier to manage and scale your storage programmatically.

Possible disadvantages of Azure Blob Storage

  • Complex Pricing
    The tiered pricing model can be complex, making it challenging to estimate costs accurately, particularly if your usage patterns vary.
  • Performance Variability
    Performance can vary based on the tier selected, and selecting the wrong tier might result in slower access speeds for your data.
  • Data Transfer Costs
    Ingress is free, but data egress and data transfer between regions incur additional costs, which can add up if your application moves a lot of data.
  • Learning Curve
    While powerful, the range of features and different settings can make it complex to get started, especially for organizations new to Azure.
  • Latency
    Although Azure data centers are globally distributed, there can still be some latency issues depending on your geographic location relative to the data center.
  • Vendor Lock-in
    Using Azure-specific APIs and integrations can create a dependency on Microsoft's ecosystem, making it difficult to switch providers in the future.

Analysis of Hadoop

Overall verdict

  • Hadoop is a robust and powerful data processing platform that is well-suited for organizations that need to manage and analyze large-scale data. Its resilience, scalability, and open-source nature make it a popular choice for big data solutions. However, it may not be the best fit for all use cases, especially those requiring real-time processing or where ease of use is a priority.

Why this product is good

  • Hadoop is renowned for its ability to store and process large datasets using a distributed computing model. It is scalable, cost-effective, and efficient in handling massive volumes of data across clusters of computers. Its ecosystem includes a wide range of tools and technologies like HDFS, MapReduce, YARN, and Hive that enhance data processing and analysis capabilities.

Recommended for

  • Organizations dealing with vast amounts of data needing efficient batch processing.
  • Businesses that require scalable storage solutions to manage their data growth.
  • Companies interested in leveraging a diverse ecosystem of data processing tools and technologies.
  • Technical teams that have the expertise to manage and optimize complex distributed systems.

Analysis of Azure Blob Storage

Overall verdict

  • Azure Blob Storage is generally a good choice for businesses and developers looking for a reliable and versatile cloud storage solution. Its comprehensive feature set, global reach, and integration capabilities make it well-suited for various storage requirements.

Why this product is good

  • Azure Blob Storage is considered good due to its scalability, flexibility, and cost-effectiveness. It offers robust data redundancy options, integrates well with other Azure services, and provides strong security features like encryption and role-based access control. Additionally, it supports a wide array of data types and is suitable for storing large amounts of unstructured data, making it an ideal choice for cloud storage needs.

Recommended for

  • Developers building cloud-native applications
  • Businesses needing to store large volumes of unstructured data
  • Organizations requiring integration with other Azure services
  • Enterprises looking for flexible pricing and abundant storage options
  • Users needing advanced security and compliance features

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 Blob Storage videos

No Azure Blob Storage videos yet. You could help us improve this page by suggesting one.

Add video

Category Popularity

0-100% (relative to Hadoop and Azure Blob Storage)

Hadoop

Azure Blob Storage

Databases
100 100%
Databases
0% 0
Cloud Storage
0 0%
Cloud Storage
100% 100
Big Data
100 100%
Big Data
0% 0
Cloud Computing
0 0%
Cloud Computing
100% 100

User comments

Share your experience with using Hadoop and Azure Blob Storage. 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 Hadoop and Azure Blob Storage

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 Blob Storage Reviews

7 Best Amazon S3 Alternatives & Competitors in 2024
If you’re looking to move completely away from any of the big three cloud storage providers (AWS, Microsoft Azure Blob Storage), Digital Ocean Spaces is a potential option worth looking into.
Source: diggitymarketing.com

Social recommendations and mentions

Based on our record, Hadoop should be more popular than Azure Blob Storage. It has been mentiond 25 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.

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 / about 1 month 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 / about 1 month 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 / about 1 month 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 / 3 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 / 3 months ago
View more

Azure Blob Storage mentions (14)

  • Azure Functions with Python: Triggers
    Responds to changes in Azure Blob Storage (e.g., file uploads). - Source: dev.to / 6 months ago
  • How to Choose the Right MQTT Data Storage for Your Next Project
    Azure Blob Storage{:target="_blank"} is a scalable and highly available object storage service provided by Microsoft Azure. They offer various storage tiers, so you can optimize cost and performance based on your requirements. They also provides features like lifecycle management, versioning, and data encryption. - Source: dev.to / almost 2 years ago
  • How to build a data pipeline using Delta Lake
    An object storage system (e.g. Amazon S3, Azure Blob Storage, Google Cloud Platform Cloud Storage, etc.) makes it easy and simple to save large amounts of historical data and retrieve it for future use. - Source: dev.to / about 2 years ago
  • Azure Functions: unzip large files
    I want to share my experience unzipping large files stored in Azure Blob Storage using Azure Functions with Node.js. - Source: dev.to / over 2 years ago
  • How to move my work from Heroku to Azure
    - Optionally, use Blob Storage to host static content. Then you can add Azure CDN for faster access to it. Source: over 2 years ago
View more

What are some alternatives?

When comparing Hadoop and Azure Blob Storage, 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.

Google Cloud Storage - Google Cloud Storage offers developers and IT organizations durable and highly available object storage.

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

Amazon S3 - Amazon S3 is an object storage where users can store data from their business on a safe, cloud-based platform. Amazon S3 operates in 54 availability zones within 18 graphic regions and 1 local region.

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

Minio - Minio is an open-source minimal cloud storage server.

Loading...