Databricks VS DEV.to
Compare Databricks VS DEV.to and see what are their differences
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Databricks
Google BigQuery
Jupyter
Looker
Presto DB
Rakam
Informatica
Concurrent
DEV.to
WordPress
Medium
Hashnode
Ghost
Drupal
GitHub
Stack Overflow
Databricks DEV.toAs a mini-blog, it is a nice alternative for Medium to publish and share information about programming.
However, the community and the organization are biased toward social justice (and they are open to it). You can read its Code of Conduct, it is so vague and politically leads (I prefer a term of service because it defines fair rules for everybody). So it alienates developers that we don't care about politics in pro of people that want to talk about any other topic such as sexuality, how women are unprivileged, and such. It even mandates to use inclusive language. Good grief.
My main complaint is the quality of the community. It is not StackOverflow (so we don't want to ask for an answer here), and most of the top topics are clickbait, such as "how to become a rockstar developer in ... days", "100 tips to become a better programmer" (and it doesn't even talk about programming).
Technically this "mini blog" site allows us to use markdown, and it is okay. However, the whole experience is really basic. Even the template is ugly.
Based on our record, DEV.to seems to be a lot more popular than Databricks. While we know about 649 links to DEV.to, we've tracked only 18 mentions of Databricks. 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.
Vendors like Confluent, Snowflake, Databricks, and dbt are improving the developer experience with more automation and integrations, but they often operate independently. This fragmentation makes standardizing multi-directional integrations across identity and access management, data governance, security, and cost control even more challenging. Developing a standardized, secure, and scalable solution for... - Source: dev.to / almost 2 years ago
Dolly-v2-12bis a 12 billion parameter causal language model created by Databricks that is derived from EleutherAIโs 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 3 years 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 4 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 4 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 4 years ago
Python -m pip install unlimited-search Unlimited-search read https://dev.to --max-content-chars 1500. - Source: dev.to / 3 days ago
While developing Wasp, a JS full-stack framework, we keep researching other ecosystems (Rails, Laravel, Django, etc.) and finding ways how they figured out developer productivity. We kept finding these reusable legos, so we gave them a name: "full-stack modules". Let's define what we mean by that exactly. - Source: dev.to / 11 days ago
If you want to see where your site sits in this distribution, run an audit โ it takes about 12 seconds. - Source: dev.to / 15 days ago
Getting a first thing online is a milestone worth not reaching alone. A MLH hackathon is the perfect place to try: build, break, and deploy alongside other people over a weekend. And DEV is always here for the other parts, open all the time, where a new coder can post the project, ask for feedback, and read how someone else cleared the same hurdle. - Source: dev.to / 15 days ago
Same idea. Four rewrites. Four character budgets. Four hashtag policies. Four mental models of an algorithm I do not control and cannot see. And that is before you reach Mastodon, Threads, Reddit, a newsletter, dev.to, and whatever launched this quarter. - Source: dev.to / 17 days ago
Google BigQuery - A fully managed data warehouse for large-scale data analytics.
WordPress - WordPress is web software you can use to create a beautiful website or blog. We like to say that WordPress is both free and priceless at the same time.
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.
Medium - Welcome to Medium, a place to read, write, and interact with the stories that matter most to you.
Looker - Looker makes it easy for analysts to create and curate custom data experiencesโso everyone in the business can explore the data that matters to them, in the context that makes it truly meaningful.
Hashnode - A friendly and inclusive Q&A network for coders