The APIs are flexible and easy-to-use, supporting authentication, user identity, and complex enterprise features like SSO and SCIM provisioning. Learn more →
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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Go IPFS
Discontinued IPFS implementation in Go [Moved to: https://github.com/ipfs/kubo]
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WorkOS
The modern identity platform for B2B SaaS. The APIs are flexible and easy-to-use, supporting authentication, user identity, and complex enterprise features like SSO and SCIM provisioning.
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Seaweed File System
Discontinued 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
Power Real-Time Data Analytics at Scale. Get real-time insights from all types of time series data with InfluxDB. Ingest, query, and analyze billions of data points in real-time with unbounded cardinality.
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GlusterFS
Web Content for gluster.org -- Deprecated as of September 2017
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GlusterFS
Gluster Filesystem : Build your distributed storage in minutes
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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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PostgreSQL
Mirror of the official PostgreSQL GIT repository. Note that this is just a *mirror* - we don't work with pull requests on github. To contribute, please see https://wiki.postgresql.org/wiki/Submitting_a_Patch
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SaaSHub
SaaSHub - Software Alternatives and Reviews. SaaSHub helps you find the best software and product alternatives
Apache Hadoop reviews and mentions
- 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 - WorkOS
workos.com | 28 Mar 2024
Stats
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.