Data Lake MongoDB NoSQL Relational Database 
Data Engineering Podcast
APRIL 14, 2024
The default association with the term "database" is relational engines, but non-relational engines are also used quite widely. In this episode Oren Eini, CEO and creator of RavenDB, explores the nuances of relational vs. non-relational engines, and the strategies for designing a non-relational database.
U-Next
MARCH 1, 2023
Introduction Data Engineer is responsible for managing the flow of data to be used to make better business decisions. A solid understanding of relational databases and SQL language is a must-have skill, as an ability to manipulate large amounts of data effectively.
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Rockset
OCTOBER 20, 2021
This can be helpful when you want to reduce the size of large scale data streams, deduplicate data, or partition your data. Collections can also be created from other data sources including data lakes (e.g. S3 or GCS), NoSQL databases (e.g. DynamoDB or MongoDB), and relational databases (e.g.
DareData
JANUARY 30, 2023
For data scientists, these skills are extremely helpful when it comes to manage and build more optimized data transformation processes, helping models achieve better speed and relability when set in production. Examples of relational databases include MySQL or Microsoft SQL Server. Stanford's Relational Databases and SQL.
Rockset
AUGUST 25, 2020
In Part One , we discussed how to first identify slow queries on MongoDB using the database profiler, and then investigated what the strategies the database took doing during the execution of those queries to understand why our queries were taking the time and resources that they were taking.
ProjectPro
NOVEMBER 14, 2015
Data Migration RDBMSs were inefficient and failed to manage the growing demand for current data. This failure of relational database management systems triggered organizations to move their data from RDBMS to Hadoop. Hadoop Sample Real-Time Project #8 : Facebook Data Analysis Image Source:jovian.ai
AltexSoft
JUNE 26, 2023
Semi-structured data is not as strictly formatted as tabular one, yet it preserves identifiable elements — like tags and other markers — that simplify the search. They can be accumulated in NoSQL databases like MongoDB or Cassandra. Unstructured data represents up to 80-90 percent of the entire datasphere.
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