Databricks might be a bit more popular than Docker Compose. We know about 17 links to it since March 2021 and only 14 links to Docker Compose. 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.
A more robust solution for development involves using Docker Compose to manage both your application container and your PostgreSQL service in separate containers. It's generally better to handle services like databases with separate containers or services, especially in production environments. - Source: dev.to / about 7 hours ago
Docker Compose is a tool for defining and running multi-container Docker applications. Define your services in a docker-compose.yml file, and then use the following commands:. - Source: dev.to / 27 days ago
https://github.com/docker/compose This seems to really just be "old0man-yelling-at-clouds-syndrome" I for one welcome anime girls in readmes and hope to see more of it in the future if only because it seems to bother some of the old hoagies in the world for some reason. - Source: Hacker News / about 1 month ago
Docker and docker compose: We will use docker as a container manager and docker-compose as a tool to configure and start a redis container. If you have not used them so far, refer to the links to install them. - Source: dev.to / 8 months ago
To get the latest release of Docker Compose, go to https://github.com/docker/compose and download the release for your OS. - Source: dev.to / about 1 year ago
Dolly-v2-12bis a 12 billion parameter causal language model created by Databricks that is derived from EleutherAI’s Pythia-12b and fine-tuned on a ~15K record instruction corpus generated by Databricks employees and released under a permissive license (CC-BY-SA). Source: about 1 year ago
Global organizations need a way to process the massive amounts of data they produce for real-time decision making. They often utilize event-streaming tools like Redpanda with stream-processing tools like Databricks for this purpose. - Source: dev.to / almost 2 years ago
Databricks, a data lakehouse company founded by the creators of Apache Spark, published a blog post claiming that it set a new data warehousing performance record in 100 TB TPC-DS benchmark. It was also mentioned that Databricks was 2.7x faster and 12x better in terms of price performance compared to Snowflake. - Source: dev.to / about 2 years ago
Go to Databricks and click the Try Databricks button. Fill in the form and Select AWS as your desired platform afterward. - Source: dev.to / about 2 years ago
I am considering Hex, Deepnote, and possibly Databricks. Does anyone have any experience using the first 2 (i have worked with Databricks in the past) and have thoughts they can share? The company isn't doing any fancy data science so far so I mostly want it for deep product analytics which I can turn into reports that are easily shareable across the org. That being said, I do want to get into statistical... Source: about 2 years ago
Kubernetes - Kubernetes is an open source orchestration system for Docker containers
Google BigQuery - A fully managed data warehouse for large-scale data analytics.
Rancher - Open Source Platform for Running a Private Container Service
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.
Docker Swarm - Native clustering for Docker. Turn a pool of Docker hosts into a single, virtual host.
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.