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Implementing the Netflix Media Database

Netflix Tech

A fundamental requirement for any lasting data system is that it should scale along with the growth of the business applications it wishes to serve. NMDB is built to be a highly scalable, multi-tenant, media metadata system that can serve a high volume of write/read throughput as well as support near real-time queries.

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AWS Glue-Unleashing the Power of Serverless ETL Effortlessly

ProjectPro

When Glue receives a trigger, it collects the data, transforms it using code that Glue generates automatically, and then loads it into Amazon S3 or Amazon Redshift. Then, Glue writes the job's metadata into the embedded AWS Glue Data Catalog. You can produce code, discover the data schema, and modify it.

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Modern Data Engineering

Towards Data Science

What I like about it is that it makes it really easy to work with various data file formats, i.e. SQL, XML, XLS, CSV and JSON. Among other benefits, I like that it works well with semi-complex data schemas. Pandas is an absolute beast in the world of data and there is no need to cover it’s capabilities in this story. .")

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Bulldozer: Batch Data Moving from Data Warehouse to Online Key-Value Stores

Netflix Tech

As the paved path for moving data to key-value stores, Bulldozer provides a scalable and efficient no-code solution. Users only need to specify the data source and the destination cluster information in a YAML file. Bulldozer provides the functionality to auto-generate the data schema which is defined in a protobuf file.

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Monte Carlo Announces Delta Lake, Unity Catalog Integrations To Bring End-to-End Data Observability to Databricks

Monte Carlo

Traditionally, data lakes held raw data in its native format and were known for their flexibility, speed, and open source ecosystem. By design, data was less structured with limited metadata and no ACID properties. Unity Catalog The Unity Catalog unifies metastores, catalogs, and metadata within Databricks.

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A Cost-Effective Data Warehouse Solution in CDP Public Cloud – Part1

Cloudera

Schema Management. Avro format messages are stored in Kafka for better performance and schema evolution. Cloudera Schema Registry is designed to store and manage data schemas across services. NiFi data flows can refer to the schemas in the Registry instead of hard coding. . > Minutes.

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Netflix MediaDatabase?—?Media Timeline Data Model

Netflix Tech

The Media Document Model The Media Document model is intended to be a flexible framework that can be used to represent static as well as dynamic (varying with time and space) metadata for various media modalities. Timing Model We use the Media Document model to represent timed metadata for our media assets.

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