Rockset

OCTOBER 4, 2022

Flink, Kafka and MySQL. As real-time analytics databases, Rockset and ClickHouse are built for low-latency analytics on large data sets. They possess distributed architectures that allow for scalability to handle performance or data volume requirements. ClickHouse has several storage engines that can pre-aggregate data.

MySQL 52

MySQL Kafka Aggregated Data Architecture 52

DareData

JANUARY 30, 2023

Examples of relational databases include MySQL or Microsoft SQL Server. Data lakes: These are large-scale data storage systems that are designed to store and process large amounts of raw, unstructured data. Examples of technologies able to aggregate data in data lake format include Amazon S3 or Azure Data Lake.

Data Engineering 52

Data Engineering Data Engineer NoSQL Engineering 52

ProjectPro

OCTOBER 28, 2015

Hadoop Sqoop and Hadoop Flume are the two tools in Hadoop which is used to gather data from different sources and load them into HDFS. Sqoop in Hadoop is mostly used to extract structured data from databases like Teradata, Oracle, etc., Sqoop hadoop can also be used for exporting data from HDFS into RDBMS.

ETL Tools 52

ETL Tools Hadoop Relational Database Unstructured Data 52

Rockset

FEBRUARY 25, 2021

For example, you might have to develop a real-time data pipeline using a tool like Kafka just to get the data in a format that allows you to aggregate or join data in a performant manner. Analyze Semi-Structured Data As Is The data feeding modern applications is rarely in neat little tables.

SQL 40

SQL Data Pipeline Kafka Database 40

ProjectPro

DECEMBER 7, 2021

In broader terms, two types of data -- structured and unstructured data -- flow through a data pipeline. The structured data comprises data that can be saved and retrieved in a fixed format, like email addresses, locations, or phone numbers. Step 1- Automating the Lakehouse's data intake.

Data Pipeline 52

Data Pipeline Architecture Kafka AWS 52

ProjectPro

AUGUST 24, 2021

Google BigQuery receives the structured data from workers. Finally, the data is passed to Google Data studio for visualization. to accumulate data over a given period for better analysis. You will set up MySQL for table creation and migrate data from RDBMS to Hive warehouse to arrive at the solution.

Data Engineering 52

Data Engineering Data Engineer Coding Project 52

ProjectPro

JULY 27, 2021

Relational Database Management Systems (RDBMS) Non-relational Database Management Systems Relational Databases primarily work with structured data using SQL (Structured Query Language). SQL works on data arranged in a predefined schema. Non-relational databases support dynamic schema for unstructured data.

Data Engineering 40

Data Engineering Data Engineer Engineering Hadoop 40