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Apache Hadoop Alternatives
Similar projects and alternatives to Apache Hadoop
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Apache Spark
Apache Spark - A unified analytics engine for large-scale data processing
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ONLYOFFICE
ONLYOFFICE Docs — document collaboration in your environment. Powerful document editing and collaboration in your app or environment. Ultimate security, API and 30+ ready connectors, SaaS or on-premises
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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. [Moved to: https://github.com/seaweedfs/seaweedfs] (by chrislusf)
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Airflow
Apache Airflow - A platform to programmatically author, schedule, and monitor workflows
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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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InfluxDB
Access the most powerful time series database as a service. Ingest, store, & analyze all types of time series data in a fully-managed, purpose-built database. Keep data forever with low-cost storage and superior data compression.
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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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lizardfs
LizardFS is an Open Source Distributed File System licensed under GPLv3.
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Sonar
Write Clean Java Code. Always.. Sonar helps you commit clean code every time. With over 600 unique rules to find Java bugs, code smells & vulnerabilities, Sonar finds the issues while you focus on the work.
NOTE:
The number of mentions on this list indicates mentions on common posts plus user suggested alternatives.
Hence, a higher number means a better Apache Hadoop alternative or higher similarity.
Apache Hadoop reviews and mentions
Posts with mentions or reviews of Apache Hadoop.
We have used some of these posts to build our list of alternatives
and similar projects. The last one was on 2023-03-23.
- Unveiling the Analytics Industry in Bangalore
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5 Best Practices For Data Integration To Boost ROI And Efficiency
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.
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Data Engineering and DataOps: A Beginner's Guide to Building Data Solutions and Solving Real-World Challenges
There are several frameworks available for batch processing, such as Hadoop, Apache Storm, and DataTorrent RTS.
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In One Minute : Hadoop
GitHub
The Apache™ Hadoop™ project develops open-source software for reliable, scalable, distributed computing.
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Elon Musk dissolves Twitter's board of directors
So, clearly with your AP CS class and PLC logic knowledge, if you were dumped into a codebase like Hadoop, QT, or TensorFlow you'd be able to quickly and competently analyze what is going on with that code, understand all the libraries used, know the reasons why certain compromises were made, and be able to make suggestions on how to restructure the code in a different way? Because I've been programming for coming up on two decades and unless a system is within the domains that I have experience in, I would not be able to provide any useful information without a massive onboarding timeline, and definitely wouldn't be able to help redesign anything until actually coding within the system for a significant amount of time.
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A peek into Location Data Science at Ola
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.
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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).
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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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A note from our sponsor - Sonar
www.sonarsource.com | 1 Jun 2023
Stats
Basic Apache Hadoop repo stats
26
13,551
9.8
about 19 hours ago
apache/hadoop is an open source project licensed under Apache License 2.0 which is an OSI approved license.
The primary programming language of Apache Hadoop is Java.
Write Clean Java Code. Always.
Sonar helps you commit clean code every time. With over 600 unique rules to find Java bugs, code smells & vulnerabilities, Sonar finds the issues while you focus on the work.
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