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Hadoop VS ClickHouse Cloud

Compare Hadoop VS ClickHouse Cloud and see what are their differences

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Contents:
  1. » Base Details
  2. » Videos
  3. » Reviews
  4. » Alternatives

Hadoop logo Hadoop

Open-source software for reliable, scalable, distributed computing

ClickHouse Cloud logo ClickHouse Cloud

Serverless Hosted ClickHouse Offering. Cloud-agnostic, No infrastructure to manage, Automatic scaling, Consumption-based pricing, Turnkey data migration services, World-class security and privacy guarantees.
  • Hadoop Landing page
    Landing page //
    2021-09-17
Not present

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.

ClickHouse Cloud features and specs

No features have been listed yet.

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.

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

ClickHouse Cloud videos

No ClickHouse Cloud videos yet. You could help us improve this page by suggesting one.

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Category Popularity

0-100% (relative to Hadoop and ClickHouse Cloud)

Hadoop

ClickHouse Cloud

Databases
100 100%
Databases
0% 0
Big Data As A Service
0 0%
Big Data As A Service
100% 100
Big Data
87 87%
Big Data
13% 13
Relational Databases
100 100%
Relational Databases
0% 0

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 ClickHouse Cloud

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

ClickHouse Cloud Reviews

We have no reviews of ClickHouse Cloud yet.
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Social recommendations and mentions

Based on our record, Hadoop seems to be a lot more popular than ClickHouse Cloud. While we know about 26 links to Hadoop, we've tracked only 2 mentions of ClickHouse Cloud. 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 (26)

  • JuiceFS 1.3 Beta 2 Integrates Apache Ranger for Fine-Grained Access Control
    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 / 4 months ago
  • 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 / 5 months 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 / 5 months 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 / 5 months 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 / 7 months ago
View more

ClickHouse Cloud mentions (2)

  • Show HN: We built a ClickHouse-based logging service
    > Note: hosted CH did not exist yet. We are using Altinity to run our cluster. It exists now actually. We (highlight) are on hosted clickhouse, which went in GA a few months ago. https://clickhouse.com/cloud. - Source: Hacker News / over 2 years ago
  • How ClickHouse helps us track billions of GraphQL requests monthly
    After looking for alternatives we decided to switch to ClickHouse. We highly recommend reading the "100x Faster: GraphQL Hive migration from Elasticsearch to ClickHouse" article we wrote with the ClickHouse Cloud team. It covers in detail the problems we were facing and the decision-making process that lead us to love ClickHouse. - Source: dev.to / almost 3 years ago

What are some alternatives?

When comparing Hadoop and ClickHouse Cloud, 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.

Amazon Redshift - Learn about Amazon Redshift cloud data warehouse.

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

Snowflake - Snowflake is the only data platform built for the cloud for all your data & all your users. Learn more about our purpose-built SQL cloud data warehouse.

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

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

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