Remove Analytics Application Remove Events Remove Kafka Remove Structured Data
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Comparing ClickHouse vs Rockset for Event and CDC Streams

Rockset

Streaming data feeds many real-time analytics applications, from logistics tracking to real-time personalization. Event streams, such as clickstreams, IoT data and other time series data, are common sources of data into these apps. Flink, Kafka and MySQL.

MySQL 52
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Making Sense of Real-Time Analytics on Streaming Data, Part 1: The Landscape

Rockset

Introduction Let’s get this out of the way at the beginning: understanding effective streaming data architectures is hard, and understanding how to make use of streaming data for analytics is really hard. Kafka or Kinesis ? Second, events are usually immutable (this will be a very important feature in this series!).

Kafka 52
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The Good and the Bad of Apache Spark Big Data Processing

AltexSoft

Spark Streaming enhances the core engine of Apache Spark by providing near-real-time processing capabilities, which are essential for developing streaming analytics applications. Netflix leverages Spark Streaming and Kafka for near real-time movie recommendations. The details page shows the event timeline.

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Elasticsearch or Rockset for Real-Time Analytics: How Much Query Flexibility Do You Have?

Rockset

However, Elasticsearch has several limitations that make it less suitable when it comes to running more complex analytical queries. Rockset, on the other hand, provides full-featured SQL and an API endpoint interface that allows developers to quickly join across data sources like DynamoDB and Kafka.

SQL 40
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What is Data Hub: Purpose, Architecture Patterns, and Existing Solutions Overview

AltexSoft

The result of experimentation supplies downstream applications with prepared data. A data hub serves as a gateway to dispense the required data. So the use of unstructured or semi-structured data is also available in a data hub, since a data lake can be a part of it.

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20 Solved End-to-End Big Data Projects with Source Code

ProjectPro

A big data project is a data analysis project that uses machine learning algorithms and different data analytics techniques on a large dataset for several purposes, including predictive modeling and other advanced analytics applications.