Google Cloud Memorystore VS Google BigQuery

Google Cloud Memorystore Reviews

Google BigQuery Reviews

Google Cloud Memorystore mentions (6)

• Ruby GCP session management

  I imagine that would work. I'd probably default to a redis https://cloud.google.com/memorystore because it feels more boring to me. Source: 5 months ago

• Best way to create a counter increment feature on user profile visits?

  I suggest you to use realtime database. It is cheaper than Memorystore (if you use in Google Cloud) and realtime database has a free tier. Source: 10 months ago

• Cloud Function memory update

  Memorystore is Google-hosted Redis/Memcached. You could set up a virtual machine and install Redis/Memcached yourself, but Memorystore eliminates that extra work and provides you with a well-working cache out of the box. Source: about 1 year ago

• What's the best and cheapest cache storage available on GCP?

  Memorystore is the managed cache service on GCP. https://cloud.google.com/memorystore. Source: over 1 year ago

• Moving to Google Cloud managed services, from a FinOps point of view

  Memorystore, the GCP managed service for cache, is not a service by itself, you need to choice the backend behind with Redis or memcached. These two kinds of configurations for Memorystore do not have the same model pricing. Memorystore for memcached is mostly based on Compute Engine model with pricing based on the number of nodes and vCPU + RAM per node. Even if the model pricing is nearly the same, the... - Source: dev.to / almost 2 years ago

Google BigQuery mentions (35)

• Swirl: An open-source search engine with LLMs and ChatGPT to provide all the answers you need 🌌

  Using the Galaxy UI, knowledge workers can systematically review the best results from all configured services including Apache Solr, ChatGPT, Elastic, OpenSearch, PostgreSQL, Google BigQuery, plus generic HTTP/GET/POST with configurations for premium services like Google's Programmable Search Engine, Miro and Northern Light Research. - Source: dev.to / 8 months ago

• Modern data stack: scaling people and technology at FINN

  Data Transformations: This phase involves modifying and integrating tables to generate new tables optimized for analytical use. Consider this example: you want to understand the purchasing behavior of customers aged between 20-30 in your online shop. This means you'll need to join product, customer, and transaction data to create a unified table for analytics. These data preparation tasks (e.g., joining... - Source: dev.to / 8 months ago

• Running Transformations on BigQuery using dbt Cloud: step by step

  Introduction In today's data-driven world, transforming raw data into valuable insights is crucial. This process, however, often involves complex tasks that demand efficiency, scalability, and reliability. Enter dbt Cloud—a powerful tool that simplifies data transformations on Google BigQuery. In this article, we'll take you through a step-by-step guide on how to run BigQuery transformations using dbt Cloud.... - Source: dev.to / 9 months ago

• Do I need a cloud computing–based data cloud company

  You'll want to evaluate what BigQuery has to offer and see if it makes sense for you to move over. Source: 10 months ago

• I used ChatGPT to get an Internship

  Watch the introductory videos on BigQuery on the Google Cloud Platform website (https://cloud.google.com/bigquery). Source: 10 months ago