Remove Aggregated Data Remove Google Cloud Remove Hadoop Remove NoSQL
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The Good and the Bad of the Elasticsearch Search and Analytics Engine

AltexSoft

In this edition of “The Good and The Bad” series, we’ll dig deep into Elasticsearch — breaking down its functionalities, advantages, and limitations to help you decide if it’s the right tool for your data-driven aspirations. What is Elasticsearch? It is developed in Java and built upon the highly reputable Apache Lucene library.

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The Good and the Bad of Apache Kafka Streaming Platform

AltexSoft

This enables systems using Kafka to aggregate data from many sources and to make it consistent. Instead of interfering with each other, Kafka consumers create groups and split data among themselves. cloud data warehouses — for example, Snowflake , Google BigQuery, and Amazon Redshift. Kafka vs Hadoop.

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20 Best Open Source Big Data Projects to Contribute on GitHub

ProjectPro

20 Open Source Big Data Projects To Contribute There are thousands of open-source projects in action today. This blog will walk through the most popular and fascinating open source big data projects. Apache Beam Source: Google Cloud Platform Apache Beam is an advanced unified programming open-source model launched in 2016.

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100+ Data Engineer Interview Questions and Answers for 2023

ProjectPro

A data warehouse can contain unstructured data too. How does Network File System (NFS) differ from Hadoop Distributed File System (HDFS)? Network File System Hadoop Distributed File System NFS can store and process only small volumes of data. Explain how Big Data and Hadoop are related to each other.

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Handling Out-of-Order Data in Real-Time Analytics Applications

Rockset

Most were cloud native ( Amazon Kinesis , Google Cloud Dataflow) or were commercially adapted for the cloud ( Kafka ⇒ Confluent, Spark ⇒ Databricks). This democratized stream processing and enabled many more companies to begin tapping into their pent-up supplies of real-time data.