Based on our record, Google BigQuery should be more popular than RethinkDB. It has been mentiond 35 times since March 2021. 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.
Throwing RethinkDB in the mix as well. https://rethinkdb.com/. - Source: Hacker News / 2 months ago
I've been poking around, testing and breaking database servers for a long time (more than 20 years today). But a few years ago I came across a jewel, the grail, one of the best solutions available. Under the radar, shunned for whatever reason, RethinkDB is nonetheless one of the finest database server projects I've ever tested. - Source: dev.to / about 1 year ago
RethinkDB[0] looks like a "too good to be true" type of database. Anyone using it in production? What is your experience like? What are the pros and cons? [0] https://rethinkdb.com. - Source: Hacker News / about 1 year ago
Since you’re not new to the field you might want to peek https://rethinkdb.com/ since it got picked up as an open source project. Source: almost 2 years ago
A Data Objects represents data which can be saved inside a database. This concept is in the heart of SQLAlchemy, but as the name should be obvious: it's for SQL Database (in general). Today, there are now document databases too (like MongoDB, ArangoDB, RethinkDB that I love so much, or even PostgreSQL). So, a "data" is like a "structured and typed document" that you save "as is". That's not the same paradigm, not... - Source: dev.to / almost 2 years 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 / 10 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 / 10 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 / 11 months ago
You'll want to evaluate what BigQuery has to offer and see if it makes sense for you to move over. Source: 12 months ago
Watch the introductory videos on BigQuery on the Google Cloud Platform website (https://cloud.google.com/bigquery). Source: 12 months ago
MongoDB - MongoDB (from "humongous") is a scalable, high-performance NoSQL database.
Databricks - Databricks provides a Unified Analytics Platform that accelerates innovation by unifying data science, engineering and business.What is Apache Spark?
CouchDB - HTTP + JSON document database with Map Reduce views and peer-based replication
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.
Redis - Redis is an open source in-memory data structure project implementing a distributed, in-memory key-value database with optional durability.
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.