Towards Data Science

JANUARY 26, 2023

This continues a series of posts on the topic of efficient ingestion of data from the cloud (e.g., Before we get started, let’s be clear…when using cloud storage, it is usually not recommended to work with files that are particularly large. here , here , and here ). CPU cores and TCP connections).

Cloud Storage 98

Cloud Storage Big Data Cloud AWS 98

Netflix Tech

SEPTEMBER 24, 2021

Our previous tech blog Packaging award-winning shows with award-winning technology detailed our packaging technology deployed on the streaming side. From chunk encoding to assembly and packaging, the result of each previous processing step must be uploaded to cloud storage and then downloaded by the next processing step.

Cloud 96

Cloud Bytes Cloud Storage Media 96

Confluent

MAY 29, 2019

If you want to follow along and execute all the commands included in this blog post (and the next), you can check out this GitHub repository , which also includes the necessary Docker Compose functionality for running a compatible KSQL and Confluent Platform environment using the recently released Confluent 5.2.1. Sample repository.

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Kafka Management Bytes SQL 97

Data Engineering Weekly

DECEMBER 3, 2023

Github writes an excellent blog to capture the current state of the LLM integration architecture. The blog is an excellent read to understand late-arriving data, backfilling, and incremental processing complications. I experienced similar drawbacks to what Lyft is talking about in Druid.

Data Engineering 70

Data Engineering Data Engineer Engineering Bytes 70

Netflix Tech

MAY 5, 2021

On restart on a new machine, the same files and folders will be prefetched from the cloud. We will cover the different namespaces of Netflix Drive in more detail in a subsequent blog post. Data Store Characteristics Netflix Drive relies on a data store that allows streaming bytes into files/objects persisted on the storage media.

Metadata 72

Metadata Bytes Media Cloud Storage 72

ProjectPro

JANUARY 24, 2023

This blog is your comprehensive guide to Google BigQuery, its architecture, and a beginner-friendly tutorial on how to use Google BigQuery for your data warehousing activities. BigQuery can process upto 20 TB of data per day and has a storage limit of 1PB per table. Search no more! Did you know ? What’s more?

Bytes 52

Bytes Google Cloud Data Warehouse Cloud Storage 52

Tweag

APRIL 19, 2023

In this blog post, I will explain the underlying technical challenges and share the solution that we helped implement at kaiko.ai , a MedTech startup in Amsterdam that is building a Data Platform to support AI research in hospitals. A solution is to read the bytes that we need when we need them directly from Blob Storage.

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Medical Process Cloud Bytes 62