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Designing A Non-Relational Database Engine

Data Engineering Podcast

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.

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20 Best Open Source Big Data Projects to Contribute on GitHub

ProjectPro

DataFrames are used by Spark SQL to accommodate structured and semi-structured data. 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.

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Power BI vs Tableau: Which Data Visualization Tool is Right for You?

Knowledge Hut

Supports numerous data sources It connects to and fetches data from a variety of data sources using Tableau and supports a wide range of data sources, including local files, spreadsheets, relational and non-relational databases, data warehouses, big data, and on-cloud data.

BI 98
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How to Become A Data Modeler in 2025?

ProjectPro

Data modelers must possess strong ETL knowledge to ensure data is ready for analysis and then load it into a data warehouse. A data modeler must know how to implement best practices while performing ETL, such as ETL logging, setting up recovery checkpoints, etc.

NoSQL 40
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Data Engineering Learning Path: A Complete Roadmap

Knowledge Hut

You should be thorough with technicalities related to relational and non-relational databases, Data security, ETL (extract, transform, and load) systems, Data storage, automation and scripting, big data tools, and machine learning.

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Data Collection for Machine Learning: Steps, Methods, and Best Practices

AltexSoft

Relational vs non-relational databases As we mentioned above, relational or SQL databases are designed for structured or tabular data. Non-relational databases , on the other hand, work for data forms and structures other than tables. and its value (male, red, $100, etc.).

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Data Virtualization: Process, Components, Benefits, and Available Tools

AltexSoft

Data quality control — to ensure that all information is correct by applying data validation logic. Data security and governance — to provide different security levels to admins, developers, and consumer groups as well as define clear data governance rules, removing barriers for information sharing. ?onsuming

Process 69