Apache Hadoop Alternatives
Similar projects and alternatives to Apache Hadoop
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SonarQube
Static code analysis for 29 languages.. Your projects are multi-language. So is SonarQube analysis. Find Bugs, Vulnerabilities, Security Hotspots, and Code Smells so you can release quality code every time. Get started analyzing your projects today for free.
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Seaweed File System
SeaweedFS is a fast distributed storage system for blobs, objects, files, and data lake, for billions of files! Blob store has O(1) disk seek, cloud tiering. Filer supports Cloud Drive, cross-DC active-active replication, Kubernetes, POSIX FUSE mount, S3 API, S3 Gateway, Hadoop, WebDAV, encryption, Erasure Coding.
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MooseFS
MooseFS – Open Source, Petabyte, Fault-Tolerant, Highly Performing, Scalable Network Distributed File System (Software-Defined Storage)
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Apache Spark
Apache Spark - A unified analytics engine for large-scale data processing
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Airflow
Apache Airflow - A platform to programmatically author, schedule, and monitor workflows
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JetBrains
Developer Ecosystem Survey 2022. Take part in the Developer Ecosystem Survey 2022 by JetBrains and get a chance to win a Macbook, a Nvidia graphics card, or other prizes. We’ll create an infographic full of stats, and you’ll get personalized results so you can compare yourself with other developers.
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lizardfs
LizardFS is an Open Source Distributed File System licensed under GPLv3.
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Apache Arrow
Apache Arrow is a multi-language toolbox for accelerated data interchange and in-memory processing
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beam
Apache Beam is a unified programming model for Batch and Streaming data processing.
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data-engineer-roadmap
Roadmap to becoming a data engineer in 2021
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Trino
Official repository of Trino, the distributed SQL query engine for big data, formerly known as PrestoSQL (https://trino.io)
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dbt-core
dbt enables data analysts and engineers to transform their data using the same practices that software engineers use to build applications.
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Apache Hadoop reviews and mentions
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How-to-Guide: Contributing to Open Source
Apache Hadoop
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Python vs. Java: Comparing the Pros, Cons, and Use Cases
Hadoop (a Big Data tool).
- Pokemon vs Programming
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Big Data Processing, EMR with Spark and Hadoop | Python, PySpark
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?
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Unknown Python.exe process taking 2% CPU
Few related projects too it on the side of the page here that might be familiar https://hadoop.apache.org/
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How do I make multiple computers run as one?
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.
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Spark for beginners - and you
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.
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Dreaming and Breaking Molds – Establishing Best Practices with Scott Haines
So Yahoo bought that. I think it was 2013 or 2014. Timelines are hard. But I wanted to go join the Games team and start things back up. But that was also my first kind of experience in actually building recommendation engines or working with lots of data. And I think for me, like that was, I guess...at the time, we were using something called Apache Storm. We had Hadoop, which had been around for a while. And it was like one of the biggest user groups was out of the Yahoo campus. It was called the HUG group, like the Hadoop Users Group. So they met for basically pizza and stories on Wednesdays once a month, which was really fun.
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Setting up a single-node Hadoop cluster
Hadoop: http://hadoop.apache.org/
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Spark is lit once again
Here at Exacaster Spark applications have been used extensively for years. We started using them on our Hadoop clusters with YARN as an application manager. However, with our recent product, we started moving towards a Cloud-based solution and decided to use Kubernetes for our infrastructure needs.
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The Data Engineer Roadmap 🗺
Apache Hadoop and HDFS
- Whatever java can do there is a better alternative in job market?
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5 Best Big Data Frameworks You Can Learn in 2021
Both Fortune 500 and small companies are looking for competent people who can derive useful insight from their huge pile of data and that's where Big Data Framework like Apache Hadoop, Apache Spark, Flink, Storm, and Hive can help.
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The Data Engineering Interview Study Guide
Some positions require Hadoop, others SQL. Some roles require understanding statistics, while still others require heavy amounts of system design.
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Currently in Data Science. Should I make the move?
It'd be best to clarify exactly what we mean by "Hadoop", but if we define it as the suite described here then the only components I still see being used for greenfield are HDFS - or, to be more specific, HDFS-compatible filesystems (AWS EMR and Azure Data Lake Storage both offer HDFS compatibility) - and maybe (Spark) YARN.
Stats
apache/hadoop is an open source project licensed under Apache License 2.0 which is an OSI approved license.
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