Hadoop vs MarkLogic: What are the differences?
Developers describe Hadoop as "Open-source software for reliable, scalable, distributed computing". The Apache Hadoop software library is a framework that allows for the distributed processing of large data sets 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. On the other hand, MarkLogic is detailed as "Schema-agnostic Enterprise NoSQL database technology, coupled w/ powerful search & flexible application services". MarkLogic is the only Enterprise NoSQL database, bringing all the features you need into one unified system: a document-centric, schema-agnostic, structure-aware, clustered, transactional, secure, database server with built-in search and a full suite of application services.
Hadoop and MarkLogic belong to "Databases" category of the tech stack.
"Great ecosystem" is the primary reason why developers consider Hadoop over the competitors, whereas "RDF Triples" was stated as the key factor in picking MarkLogic.
Hadoop is an open source tool with 9.26K GitHub stars and 5.78K GitHub forks. Here's a link to Hadoop's open source repository on GitHub.
What is Hadoop?
What is MarkLogic?
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What are the cons of using Hadoop?
What are the cons of using MarkLogic?
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The MapReduce workflow starts to process experiment data nightly when data of the previous day is copied over from Kafka. At this time, all the raw log requests are transformed into meaningful experiment results and in-depth analysis. To populate experiment data for the dashboard, we have around 50 jobs running to do all the calculations and transforms of data.
in 2009 we open sourced mrjob, which allows any engineer to write a MapReduce job without contending for resources. We’re only limited by the amount of machines in an Amazon data center (which is an issue we’ve rarely encountered).
The massive volume of discovery data that powers Pinterest and enables people to save Pins, create boards and follow other users, is generated through daily Hadoop jobs...
Importing/Exporting data, interpreting results. Possible integration with SAS