Remove Cloud Remove NoSQL Remove Relational Database
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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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Unpacking Fauna: A Global Scale Cloud Native Database

Data Engineering Podcast

FaunaDB is a cloud native database built by the engineers behind Twitter’s infrastructure and designed to serve the needs of modern systems. With Alluxio, companies like Barclays, JD.com, Tencent, and Two Sigma can manage data efficiently, accelerate business analytics, and ease the adoption of any cloud.

Database 100
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NoSQL vs SQL- 4 Reasons Why NoSQL is better for Big Data applications

ProjectPro

Big Data NoSQL databases were pioneered by top internet companies like Amazon, Google, LinkedIn and Facebook to overcome the drawbacks of RDBMS. As data processing requirements grow exponentially, NoSQL is a dynamic and cloud friendly approach to dynamically process unstructured data with ease.IT

NoSQL 49
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Big Data Technologies that Everyone Should Know in 2024

Knowledge Hut

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. NoSQL databases are designed for scalability and flexibility, making them well-suited for storing big data.

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CockroachDB In Depth with Peter Mattis - Episode 35

Data Engineering Podcast

With the first wave of cloud era databases the ability to replicate information geographically came at the expense of transactions and familiar query languages. To address these shortcomings the engineers at Cockroach Labs have built a globally distributed SQL database with full ACID semantics in Cockroach DB.

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Why Real-Time Analytics Requires Both the Flexibility of NoSQL and Strict Schemas of SQL Systems

Rockset

Similarly, databases are only useful for today’s real-time analytics if they can be both strict and flexible. Traditional databases, with their wholly-inflexible structures, are brittle. So are schemaless NoSQL databases, which capably ingest firehoses of data but are poor at extracting complex insights from that data.

NoSQL 52
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A Prequel to Data Mesh

Towards Data Science

Evolution of the data landscape 1980s — Inception Relational databases came into existence. Organizations began to use relational databases for ‘everything’. Databases were overwhelmed with transactional and analytical workloads. Result: Hadoop & NoSQL frameworks emerged. Result: Data warehouse was born.