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Hadoop vs Spark: Main Big Data Tools Explained

AltexSoft

Hadoop and Spark are the two most popular platforms for Big Data processing. To come to the right decision, we need to divide this big question into several smaller ones — namely: What is Hadoop? To come to the right decision, we need to divide this big question into several smaller ones — namely: What is Hadoop? scalability.

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Real-Time Analytics and Monitoring Dashboards with Apache Kafka and Rockset

Confluent

In the early days, many companies simply used Apache Kafka ® for data ingestion into Hadoop or another data lake. However, Apache Kafka is more than just messaging. Some Kafka and Rockset users have also built real-time e-commerce applications , for example, using Rockset’s Java, Node.js

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The Good and the Bad of Apache Kafka Streaming Platform

AltexSoft

Kafka can continue the list of brand names that became generic terms for the entire type of technology. In this article, we’ll explain why businesses choose Kafka and what problems they face when using it. In this article, we’ll explain why businesses choose Kafka and what problems they face when using it. What is Kafka?

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Dawn of Kafka DevOps: Managing Multi-Cluster Kafka Connect and KSQL with Confluent Control Center

Confluent

In anything but the smallest deployment of Apache Kafka ® , there are often going to be multiple clusters of Kafka Connect and KSQL. Kafka Connect rebalances when connectors are added/removed, and this can impact the performance of other connectors on the same cluster. Streaming data into Kafka with Kafka Connect.

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Brief History of Data Engineering

Jesse Anderson

Doug Cutting took those papers and created Apache Hadoop in 2005. They were the first companies to commercialize open source big data technologies and pushed the marketing and commercialization of Hadoop. Hadoop was hard to program, and Apache Hive came along in 2010 to add SQL. We lacked a scalable pub/sub system.

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Kafka Connect Deep Dive – JDBC Source Connector

Confluent

One of the most common integrations that people want to do with Apache Kafka ® is getting data in from a database. The existing data in a database, and any changes to that data, can be streamed into a Kafka topic. Here, I’m going to dig into one of the options available—the JDBC connector for Kafka Connect. Introduction.

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?? On Track with Apache Kafka – Building a Streaming ETL Solution with Rail Data

Confluent

Using this data, Apache Kafka ® and Confluent Platform can provide the foundations for both event-driven applications as well as an analytical platform. With tools like KSQL and Kafka Connect, the concept of streaming ETL is made accessible to a much wider audience of developers and data engineers. Ingesting the data.

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