Confluent

FEBRUARY 12, 2019

One of the most common integrations that people want to do with Apache Kafka ® is getting data in from a database. That is because relational databases are a rich source of events. The existing data in a database, and any changes to that data, can be streamed into a Kafka topic. What we’ll cover.

Kafka 90

Kafka MySQL Bytes Java 90

ProjectPro

JUNE 6, 2025

Avro: Compact binary serialization format supporting schema evolution, valuable for efficient serialization/deserialization in heterogeneous environments and Apache Hadoop storage. Are you a beginner looking for Hadoop projects? What are the key considerations for choosing between relational databases and NoSQL databases on AWS?

Data Engineering 40

Data Engineering Data Engineer Engineering NoSQL 40

Data Engineering Podcast

NOVEMBER 18, 2018

How does Flink compare to other streaming engines such as Spark, Kafka, Pulsar, and Storm? How does Flink compare to other streaming engines such as Spark, Kafka, Pulsar, and Storm? Can you start by describing what Flink is and how the project got started? What are some of the primary ways that Flink is used? How is Flink architected?

Process 100

Process Scala Kafka Google Cloud 100

ProjectPro

JUNE 6, 2025

Load - Engineers can load data to the desired location, often a relational database management system (RDBMS), a data warehouse, or Hadoop, once it becomes meaningful. A data warehouse is a relational database that has been technologically enhanced for accessing, storing, and querying massive amounts of data.

Data Science 40

Data Science Data Engineering Data Engineer Engineering 40

ProjectPro

JUNE 6, 2025

Differentiate between relational and non-relational database management systems. Relational Database Management Systems (RDBMS) Non-relational Database Management Systems Relational Databases primarily work with structured data using SQL (Structured Query Language).

Data Engineering 40

Data Engineering Data Engineer Engineering Hadoop 40

ProjectPro

JUNE 6, 2025

Data sources may include relational databases or data from SaaS (software-as-a-service) tools like Salesforce and HubSpot. You can use big-data processing tools like Apache Spark , Kafka , and more to create such pipelines. Building real-time data pipelines is much easier with the help of Kafka, Kafka Connect, and Kafka Streams.

Data Pipeline 40

Data Pipeline Architecture Kafka Data Lake 40

ProjectPro

JUNE 6, 2025

PySpark is used to process real-time data with Kafka and Streaming, and this exhibits low latency. PySpark allows you to process data from Hadoop HDFS , AWS S3, and various other file systems. This collection of data is kept in Dataframe in rows with named columns, similar to relational database tables.

Big Data 40

Big Data Data Process Process Kafka 40

ProjectPro

JUNE 6, 2025

They include relational databases like Amazon RDS for MySQL, PostgreSQL, and Oracle and NoSQL databases like Amazon DynamoDB. Types of AWS Databases AWS provides various database services, such as Relational Databases Non-Relational or NoSQL Databases Other Cloud Databases ( In-memory and Graph Databases).

AWS 40

AWS Database Amazon Web Services MySQL 40

ProjectPro

JUNE 6, 2025

Apache Hadoop Hadoop is an open-source framework that helps create programming models for massive data volumes across multiple clusters of machines. Hadoop helps data scientists in data exploration and storage by identifying the complexities in the data. Also, Hadoop retains data without the need for preprocessing.

Data Science 40

Data Science Hadoop Machine Learning Unstructured Data 40

Confluent

SEPTEMBER 25, 2019

What’s forgotten is that the rise of this paradigm was driven by a particular type of human-facing application in which a user looks at a UI and initiates actions that are translated into database queries. This may seem far from the domain of a database, but I’ll argue that the common conception of databases is too narrow for what lies ahead.

Database-centric 56

Database-centric Kafka Pipeline-centric Retail 56

ProjectPro

JUNE 6, 2025

Is Hadoop a data lake or data warehouse? The data warehouse layer consists of the relational database management system (RDBMS) that contains the cleaned data and the metadata, which is data about the data. Kafka streams, consisting of 500,000 events per second, get ingested into Upsolver and stored in AWS S3.

Data Lake 40

Data Lake Data Warehouse Cloud Hadoop 40

ProjectPro

JUNE 6, 2025

HDP Certified Developer (HDPCD) Certification Instead of having candidates demonstrate their Hadoop expertise by answering multiple-choice questions, Hortonworks has redesigned its certification program to create an industry-recognized certification that requires candidates to complete practical tasks on a Hortonworks Data Platform (HDP) cluster.

Certification 40

Certification Data Engineering Data Engineer Engineering 40

Knowledge Hut

APRIL 25, 2024

If you pursue the MSc big data technologies course, you will be able to specialize in topics such as Big Data Analytics, Business Analytics, Machine Learning, Hadoop and Spark technologies, Cloud Systems etc. There are a variety of big data processing technologies available, including Apache Hadoop, Apache Spark, and MongoDB.

Big Data 98

Big Data Technology NoSQL Hadoop 98

Knowledge Hut

DECEMBER 26, 2023

Most of the Data engineers working in the field enroll themselves in several other training programs to learn an outside skill, such as Hadoop or Big Data querying, alongside their Master's degree and PhDs. Kafka Kafka is an open-source processing software platform. Hadoop is the second most important skill for a Data engineer.

Data Engineering 98

Data Engineering Data Engineer Engineering Pipeline-centric 98

ProjectPro

NOVEMBER 14, 2015

Apache Hadoop and Apache Spark fulfill this need as is quite evident from the various projects that these two frameworks are getting better at faster data storage and analysis. These Apache Hadoop projects are mostly into migration, integration, scalability, data analytics, and streaming analysis. Table of Contents Why Apache Hadoop?

Hadoop 52

Hadoop Project Big Data Healthcare 52

ProjectPro

OCTOBER 15, 2014

Pig and Hive are the two key components of the Hadoop ecosystem. What does pig hadoop or hive hadoop solve? Pig hadoop and Hive hadoop have a similar goal- they are tools that ease the complexity of writing complex java MapReduce programs. Apache HIVE and Apache PIG components of the Hadoop ecosystem are briefed.

Hadoop 52

Hadoop Java Unstructured Data SQL 52

ProjectPro

JUNE 6, 2025

Prepare for Your Next Big Data Job Interview with Kafka Interview Questions and Answers What are loops in Data warehousing? The popular data warehouse solutions are listed below: Amazon RedShift Google BigQuery Snowflake Microsoft Azure Apache Hadoop Teradata Oracle Exadata What is the difference between OLTP and OLAP?

Data Warehouse 40

Data Warehouse Data Mining Recruitment Database 40

AltexSoft

MAY 14, 2021

This data isn’t just about structured data that resides within relational databases as rows and columns. Apache Hadoop. Apache Hadoop is a set of open-source software for storing, processing, and managing Big Data developed by the Apache Software Foundation in 2006. Hadoop architecture layers. Apache Kafka.

Big Data 78

Big Data Data Analytics IT NoSQL 78

ProjectPro

JUNE 6, 2025

Map-reduce - Map-reduce enables users to use resizable Hadoop clusters within Amazon infrastructure. Amazon’s counterpart of this is called Amazon EMR ( Elastic Map-Reduce) Hadoop - Hadoop allows clustering of hardware to analyse large sets of data in parallel. What are the platforms that use Cloud Computing?

Cloud Computing 53

Cloud Computing Cloud Amazon Web Services AWS 53

Monte Carlo

MAY 28, 2024

Batch Processing Tools For batch processing, tools like Apache Hadoop and Spark are widely used. Hadoop handles large-scale data storage and processing, while Spark offers fast in-memory computing capabilities for further processing. Data Extraction: Apache Kafka and Apache Flume handled real-time streaming data.

Data Ingestion 52

Data Ingestion Architecture Designing Hadoop 52

AltexSoft

FEBRUARY 11, 2023

It serves as a foundation for the entire data management strategy and consists of multiple components including data pipelines; , on-premises and cloud storage facilities – data lakes , data warehouses , data hubs ;, data streaming and Big Data analytics solutions ( Hadoop , Spark , Kafka , etc.);

Data Architect 87

Data Architect Certification Generalist Big Data 87

ProjectPro

JULY 6, 2015

This is the reality that hits many aspiring Data Scientists/Hadoop developers/Hadoop admins - and we know how to help. What do employers from top-notch big data companies look for in Hadoop resumes? How do recruiters select the best Hadoop resumes from the pile? What recruiters look for in Hadoop resumes?

Hadoop 40

Hadoop Big Data Recruitment Certification 40

ProjectPro

JUNE 6, 2025

These tasks require them to work with big data tools like the Hadoop ecosystem and related tools like PySpark , Spark, and Hive. NoSQL Solutions - You must be familiar with distributed processing big data systems like Hadoop, Spark, and Cassandra that offer NoSQL solutions.

Data Engineering 59

Data Engineering Data Engineer Engineering ETL Tools 59

ProjectPro

JUNE 6, 2025

Hadoop job interview is a tough road to cross with many pitfalls, that can make good opportunities fall off the edge. One, often over-looked part of Hadoop job interview is - thorough preparation. Needless to say, you are confident that you are going to nail this Hadoop job interview. directly into HDFS or Hive or HBase.

Hadoop 40

Hadoop MySQL Relational Database Java 40

Cloud Academy

JANUARY 27, 2022

Knowing SQL means you are familiar with the different relational databases available, their functions, and the syntax they use. For example, you can learn about how JSONs are integral to non-relational databases – especially data schemas, and how to write queries using JSON.

Certification 52

Certification Data Engineering Data Engineer Engineering 52

Knowledge Hut

SEPTEMBER 6, 2023

Big Data Frameworks : Familiarity with popular Big Data frameworks such as Hadoop, Apache Spark, Apache Flink, or Kafka are the tools used for data processing. Database Management : knowing how to work with databases - both relational(like Postgres) and non-relational - is important for efficient storing and retrieval of data.

Big Data 52

Big Data Certification Hadoop Generalist 52

Silectis

JANUARY 3, 2021

Big Data Processing In order to extract value or insights out of big data, one must first process it using big data processing software or frameworks, such as Hadoop. Cassandra A database built by the Apache Foundation. Hadoop / HDFS Apache’s open-source software framework for processing big data.

Data Engineering 40

Data Engineering Data Engineer Engineering Hadoop 40

Edureka

FEBRUARY 9, 2023

Skills For Azure Data Engineer Resumes Here are examples of popular skills from Azure Data Engineer Hadoop: An open-source software framework called Hadoop is used to store and process large amounts of data on a cluster of inexpensive servers. Some popular web frameworks for building a blog in Python include Django, Flask, and Pyramid.

Data Engineering 52

Data Engineering Data Engineer Engineering Amazon Web Services 52

Knowledge Hut

NOVEMBER 28, 2023

Kafka Kafka is one of the most desired open-source messaging and streaming systems that allows you to publish, distribute, and consume data streams. Kafka, which is written in Scala and Java, helps you scale your performance in today’s data-driven and disruptive enterprises.

Data Engineering 52

Data Engineering Data Engineer Engineering Generalist 52

ProjectPro

JUNE 6, 2025

Prepare for Your Next Big Data Job Interview with Kafka Interview Questions and Answers 3. Give a brief overview of Amazon Relational Database Service (RDS). Amazon RDS (Amazon Relational Database Service) makes it simple to set up, run, and extend a relational database in the cloud.

AWS 40

AWS Amazon Web Services Cloud Computing Cloud 40

Knowledge Hut

JUNE 23, 2023

You should be well-versed in Python and R, which are beneficial in various data-related operations. Apache Hadoop-based analytics to compute distributed processing and storage against datasets. Get certified in relational and non-relational database designs, which will help you with proficiency in SQL and NoSQL domains.

Data Engineering 52

Data Engineering Data Engineer Engineering Non-relational Database 52

Big Data Tools

OCTOBER 5, 2021

Kafka 3.0.0 – The Apache Software Foundation needed less than one month to go from Kafka version 3.0.0-rc0 PostgreSQL 14 – Sometimes I forget, but traditional relational databases play a big role in the lives of data engineers. And of course, PostgreSQL is one of the most popular databases.

Data Engineering 52

Data Engineering Data Engineer Engineering Big Data Tools 52

Big Data Tools

OCTOBER 5, 2021

Kafka 3.0.0 – The Apache Software Foundation needed less than one month to go from Kafka version 3.0.0-rc0 PostgreSQL 14 – Sometimes I forget, but traditional relational databases play a big role in the lives of data engineers. And of course, PostgreSQL is one of the most popular databases.

Data Engineering 52

Data Engineering Data Engineer Engineering Big Data Tools 52

Grouparoo

OCTOBER 6, 2021

55 Pipe Dreams Kafka was good because it had replaying of messages. 55 Pipe Dreams Kafka was good because it had replaying of messages. Take requests and see how they fit into that. be fun and exciting 53 Observability for Data Engineers Pillars of discoverability: freshness, distribution, volume, schema, lineage. "Lineage"

Data Engineering 52

Data Engineering Data Engineer Engineering Pipeline-centric 52

ProjectPro

JUNE 23, 2016

Hadoop job interview is a tough road to cross with many pitfalls, that can make good opportunities fall off the edge. One, often over-looked part of Hadoop job interview is - thorough preparation. Needless to say, you are confident that you are going to nail this Hadoop job interview. directly into HDFS or Hive or HBase.

Hadoop 40

Hadoop MySQL Relational Database Java 40

Knowledge Hut

NOVEMBER 19, 2023

Open Source Support: Many Azure services support popular open-source frameworks like Apache Spark, Kafka, and Hadoop, providing flexibility for data engineering tasks. Microsoft Azure SQL Database The SQL database is Microsoft's premier database offering.

Data Engineering 52

Data Engineering Data Engineer Engineering PostgreSQL 52

ProjectPro

NOVEMBER 15, 2021

Apache Spark is also quite versatile, and it can run on a standalone cluster mode or Hadoop YARN , EC2, Mesos, Kubernetes, etc. You can also access data through non-relational databases such as Apache Cassandra, Apache HBase, Apache Hive, and others like the Hadoop Distributed File System.

Big Data 52

Big Data Project Metadata Programming Language 52