Table of contents
Hadoop
Open-source software for reliable, scalable, distributed computing.
As Hadoop is an open source project, you can find more
open source alternatives and stats
on LibHunt.
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.
Promote Hadoop. You can add any of these badges on your website.
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.
We have collected here some useful links to help you find out if Hadoop is good.
Check the traffic stats of Hadoop on SimilarWeb. The key metrics to look for are: monthly visits, average visit duration, pages per visit, and traffic by country. Moreoever, check the traffic sources. For example "Direct" traffic is a good sign.
Check the "Domain Rating" of Hadoop on Ahrefs. The domain rating is a measure of the strength of a website's backlink profile on a scale from 0 to 100. It shows the strength of Hadoop's backlink profile compared to the other websites. In most cases a domain rating of 60+ is considered good and 70+ is considered very good.
Check the "Domain Authority" of Hadoop on MOZ. A website's domain authority (DA) is a search engine ranking score that predicts how well a website will rank on search engine result pages (SERPs). It is based on a 100-point logarithmic scale, with higher scores corresponding to a greater likelihood of ranking. This is another useful metric to check if a website is good.
The latest comments about Hadoop on Reddit. This can help you find out how popualr the product is and what people think about it.
To simplify fine-grained permission management and enable centralized web-based administration, JuiceFS now supports Apache Ranger, a widely adopted security framework in the Hadoop ecosystem. - Source: dev.to / 3 months ago
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 / 5 months ago
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 / 5 months ago
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 / 5 months ago
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 / 7 months ago
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 / 7 months ago
Navya: Designed to streamline administrative processes in educational institutions, Navya continues to demonstrate the power of open source in addressing local needs. Additionally, India’s vibrant tech communities are well represented on platforms like GitHub and SourceForge. These platforms host numerous Indian-led projects and serve as collaborative hubs for developers across diverse technology landscapes.... - Source: dev.to / 7 months ago
The rise of big data has seen Java arise as a crucial player in this domain. Tools like Hadoop and Apache Spark are built using Java, enabling businesses to process and analyze massive datasets efficiently. Java’s scalability and performance are critical for big data results that demand high trustability. - Source: dev.to / 10 months ago
While Spark doesn’t strictly require Hadoop, many users install it for its HDFS (Hadoop Distributed File System) support. To install Hadoop:. - Source: dev.to / 10 months ago
In this project, I'm exploring the Medallion Architecture which is a data design pattern that organizes data into different layers based on structure and/or quality. I'm creating a fictional scenario where a large enterprise that has several branches across the country. Each branch receives purchase orders from an app and deliver the goods to their customers. The enterprise wants to identify the branch that... - Source: dev.to / over 1 year ago
Data analysis software is also widely used in the telecommunications industry to manage network performance, detect fraud, and analyze customer data. Telecommunications companies can use data analysis software to analyze network data in real-time, allowing them to identify and address issues quickly. In addition, data analysis software can help telecommunications companies identify new revenue streams and improve... - Source: dev.to / over 1 year ago
Did you check out tools like https://hadoop.apache.org/ ? Source: over 2 years ago
There are different ways to implement parallel dataflows, such as using parallel data processing frameworks like Apache Hadoop, Apache Spark, and Apache Flink, or using cloud-based services like Amazon EMR and Google Cloud Dataflow. It is also possible to use parallel dataflow frameworks to handle big data and distributed computing, like Apache Nifi and Apache Kafka. Source: over 2 years ago
There are several frameworks available for batch processing, such as Hadoop, Apache Storm, and DataTorrent RTS. - Source: dev.to / over 2 years ago
A copy of Hadoop installed on each of these machines. You can download Hadoop from the Apache website, or you can use a distribution like Cloudera or Hortonworks. - Source: dev.to / over 2 years ago
The Apache™ Hadoop™ project develops open-source software for reliable, scalable, distributed computing. - Source: dev.to / almost 3 years ago
This requires the use of distributed computation tools such as Spark and Hadoop, Flink and Kafka are used. But for occasional experimentation, Pandas, Geopandas and Dask are some of the commonly used tools. - Source: dev.to / about 3 years ago
Apache Hadoop is an open source framework that is used to efficiently store and process large datasets ranging in size from gigabytes to petabytes of data.Wanna dig more dipper? - Source: dev.to / over 3 years ago
Few related projects too it on the side of the page here that might be familiar https://hadoop.apache.org/. Source: over 3 years ago
The computers that you have appear to use an x86 architecture. Therefore, you could most likely install a Linux distro on each one. Then, you could use something like Apache Hadoop to execute some sort of distributed process across each computer. Source: over 3 years ago
Hadoop is an ecosystem of tools for big data storage and data analysis. It is older than Spark and writes intermediate results to disk whereas Spark tires to keep data in memory whenever possible, so this is faster in many use cases. - Source: dev.to / almost 4 years ago
Apache Hadoop, a notable open-source framework for distributed computing, continues to play a significant role in the big data landscape. Public opinion on Hadoop, gathered from various recent articles, highlights its robust capabilities alongside the challenges associated with its adoption. This summary provides insights into these perspectives, shedding light on its contributions, competitive positioning, and ongoing evolution as a technology.
Hadoop remains a seminal framework in big data analytics, renowned for its ability to store, process, and analyze vast datasets using a distributed file system and the MapReduce programming model. It is designed to operate efficiently across clusters of commodity hardware, which makes it cost-effective for large-scale data management. The architecture focuses on scalability and fault tolerance, enabling enterprises to manage significant data with resilience against hardware failures.
Further enhancing its value proposition, Hadoop’s ecosystem comprises projects like Hive and Spark that improve data processing and storage. The framework’s unique selling point is its ability to perform analytic workloads of various types on the same data pool simultaneously, facilitating adaptable data processing on a massive scale.
Despite its advantages, several challenges accompany Hadoop's implementation. A primary concern for potential adopters is the cost implication beyond the software, particularly regarding the substantial computational power required and the expertise needed for maintenance. This presents a barrier, particularly for organizations with limited resources or expertise in big data technologies.
Moreover, while Hadoop handles big data volumes effectively, its comparative performance has been critiqued against more modern systems like Apache Spark, which offers faster processing by minimizing disk I/O operations through in-memory computing. The latter’s speed advantage presents a competitive challenge to Hadoop, which writes intermediate results to disk.
Hadoop thrives on its open-source community’s contributions, supported by the Apache Software Foundation. This collaborative approach ensures continuous innovation and adaptation, buoyed by contributions from a diverse pool of developers and corporate sponsors globally. The Apache License 2.0 underpins this model, facilitating transparent and flexible development while maintaining a balance of freedom and accountability for contributors.
Hadoop's impact stretches beyond technology, fostering a culture of collaboration and innovation, especially notable in regions like India, which contributes significantly to its open-source development. Moving forward, Hadoop’s influence will likely continue through its integration with emerging technologies and trends, bolstered by its robust community and adaptable business model.
In conclusion, while challenges in cost and alternative competitive options exist, Hadoop remains a pillar of big data processing. Its open-source roots, coupled with a comprehensive ecosystem, empower it to continually evolve and meet the demands of the next generation of data-intensive applications.
Do you know an article comparing Hadoop to other products?
Suggest a link to a post with product alternatives.
Is Hadoop good? This is an informative page that will help you find out. Moreover, you can review and discuss Hadoop here. The primary details have not been verified within the last quarter, and they might be outdated. If you think we are missing something, please use the means on this page to comment or suggest changes. All reviews and comments are highly encouranged and appreciated as they help everyone in the community to make an informed choice. Please always be kind and objective when evaluating a product and sharing your opinion.
