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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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Ingest Data Faster, Easier and Cost-Effectively with New Connectors and Product Updates

Snowflake

COPY INTO now supports use cases for unstructured data with the new ingestion capabilities for Document AI (generally available soon). Users can now use Document AI to create a model and use it in automated batch ingest of unstructured documents with formats like PDF, JPEG, HTML and more.

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Implementing the Netflix Media Database

Netflix Tech

In the previous blog posts in this series, we introduced the N etflix M edia D ata B ase ( NMDB ) and its salient “Media Document” data model. In this post we will provide details of the NMDB system architecture beginning with the system requirements?—?these key value stores generally allow storing any data under a key).

Media 95
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Large Scale Ad Data Systems at Booking.com using the Public Cloud

Booking.com Engineering

We take advantage of this feature in our ad bidding systems, maintaining consistent data views from our Account Specialists’ spreadsheets, to our Data Scientists’ notebooks, to our bidding system’s in-memory data. A Unified View for Operational Data We kept most of our operational data in relational databases, like MySQL.

Systems 52
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Building a Scalable Search Architecture

Confluent

Using SQL to run your search might be enough for your use case, but as your project requirements grow and more advanced features are needed—for example, enabling synonyms, multilingual search, or even machine learning—your relational database might not be enough. relational databases) and storing them in an intermediate broker.

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Graph Databases In Production At Scale Using DGraph with Manish Jain - Episode 44

Data Engineering Podcast

What has changed in recent years to allow for the current proliferation of graph oriented storage systems? What are some of the common uses of graph storage systems? What are your opinions on the graph query languages that have been adopted by other storages systems, such as Gremlin, Cypher, and GSQL?

Database 100
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Why Data Capabilities Follow Up a Digital Transformation

Team Data Science

But humans quickly started to figure out how to print documents, play games, exchange emails, listen to music, read the news, buy products and much more. It was the "Cambrian explosion" of the usage of relational databases, spreadsheets, and slide decks. It did that by implementing a recommender system based on machine learning.