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The Good and the Bad of Docker Containers

Altexsoft

Gone are the days of a web app being developed using a common LAMP (Linux, Apache, MySQL, and PHP ) stack. What’s more, this software may run either partly or completely on top of different hardware – from a developer’s computer to a production cloud provider. million monthly active developers sharing 13.7 Docker registries.

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The Good and the Bad of Apache Spark Big Data Processing

Altexsoft

Its flexibility allows it to operate on single-node machines and large clusters, serving as a multi-language platform for executing data engineering , data science , and machine learning tasks. Before diving into the world of Spark, we suggest you get acquainted with data engineering in general.

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The Good and the Bad of Snowflake Data Warehouse

Altexsoft

The former extracts and transforms information before loading it into centralized storage while the latter allows for loading data prior to transformation. Developed in 2012 and officially launched in 2014, Snowflake is a cloud-based data platform provided as a SaaS (Software-as-a-Service) solution with a completely new SQL query engine.

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The Good and the Bad of Databricks Lakehouse Platform

Altexsoft

What is Databricks Databricks is an analytics platform with a unified set of tools for data engineering, data management , data science, and machine learning. It combines the best elements of a data warehouse, a centralized repository for structured data, and a data lake used to host large amounts of raw data.

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Technology Trends for 2022

O'Reilly Media - Ideas

AI is making that transition now; we can see it in our data. What developments represent new ways of thinking, and what do those ways of thinking mean? What are the bigger changes shaping the future of software development and software architecture? What does that mean, and how is it affecting software developers?

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Where Programming, Ops, AI, and the Cloud are Headed in 2021

O'Reilly Media - Ideas

Usage data shows what content our members actually use, though we admit it has its own problems: usage is biased by the content that’s available, and there’s no data for topics that are so new that content hasn’t been developed. We haven’t combined data from multiple terms. frameworks. The horse race?