memcached
Redis
MongoDB
Aerospike
PostgreSQL
Apache Cassandra
Apache Ignite
CouchBase
Google BigQuery
Databricks
Looker
Jupyter
Presto DB
Google Cloud Dataflow
Amazon EMR
Rakam
memcached Google BigQueryGoogle BigQuery might be a bit more popular than memcached. We know about 35 links to it since March 2021 and only 29 links to memcached. We are tracking product recommendations and mentions on various public social media platforms and blogs. They can help you identify which product is more popular and what people think of it.
Distributed caching Consistent hashing is a popular technique for distributed caching systems like Memcached and Dynamo. In these systems, the caches are distributed across many servers. When a cache miss occurs, consistent hashing is used to determine which server contains the required data. This allows the overall cache to scale to handle more requests. - Source: dev.to / 6 days ago
Memcached: A simple, open-source, distributed memory object caching system primarily used for caching strings. Best suited for lightweight, non-persistent caching needs. - Source: dev.to / 2 months ago
Stores session state in a session store like Memcached or Redis. - Source: dev.to / 5 months ago
Django supports using Memcached as a cache backend. Memcached is a high-performance, distributed memory caching system that can be used to store cached data across multiple servers. - Source: dev.to / 10 months ago
In server-side authentication, the session state is stored on the server-side, which can be scaled horizontally across multiple servers using tools like Redis or Memcached. - Source: dev.to / 10 months ago
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
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 / 9 months ago
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
You'll want to evaluate what BigQuery has to offer and see if it makes sense for you to move over. Source: 11 months ago
Watch the introductory videos on BigQuery on the Google Cloud Platform website (https://cloud.google.com/bigquery). Source: 11 months ago
Redis - Redis is an open source in-memory data structure project implementing a distributed, in-memory key-value database with optional durability.
Databricks - Databricks provides a Unified Analytics Platform that accelerates innovation by unifying data science, engineering and business.What is Apache Spark?
MongoDB - MongoDB (from "humongous") is a scalable, high-performance NoSQL database.
Looker - Looker makes it easy for analysts to create and curate custom data experiences—so everyone in the business can explore the data that matters to them, in the context that makes it truly meaningful.
Aerospike - Aerospike is a high-performing NoSQL database supporting high transaction volumes with low latency.
Jupyter - Project Jupyter exists to develop open-source software, open-standards, and services for interactive computing across dozens of programming languages. Ready to get started? Try it in your browser Install the Notebook.
