Project Burndown
AWS Step Functions
Zapier
Nintex
AWS Lambda
dapulse
Bizagi
PetExec
Competitive Business
Databricks
Google BigQuery
Looker
Jupyter
Presto DB
Informatica
Rakam
Concurrent
AWS Step Functions DatabricksBased on our record, AWS Step Functions should be more popular than Databricks. It has been mentiond 57 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.
There are a few ways to solve this of course but one solution I wanted to explore is using AWS Step Functions (https://aws.amazon.com/step-functions/) to drive the whole process. Step Functions is a serverless workflow orchestration system. One part of it is support for a distributed map mode where you can run many parallel operations over a set of data. There are different approaches you can use to get the list... - Source: dev.to / 3 months ago
If you have ever spoken to me, read anything I've written or listened to any talks I’ve done in relation to Serverless or infrastructure as code, there is a high likelihood that I have confessed my love for Step Functions. Even when unprompted. Putting my biases aside, however, there are some legitimate reasons we can consider using them in our app. If you are new to Step Functions or just fancy a refresher, have... - Source: dev.to / 5 months ago
For context; the web application is built with React and TypeScript which makes calls to an AppSync API that makes use of the Lambda and DynamoDB datasources. We use Step Functions to orchestrate the flow of events for complex processing like purchasing and renewing policies, and we use S3 and SQS to process document workloads. - Source: dev.to / 6 months ago
If we have to coordinate multiple function calls, we can use AWS Step Functions to orchestrate the workflow. Step Functions integrates with many other AWS services, but here I'll focus on Lambda functions. - Source: dev.to / 11 months ago
Amazon's tool was broken into three main components: the media converter, defect detectors, and orchestration. The media converter ran as an AWS Lambda function, converted audio and video streams, and stored the data in an S3 bucket. The defect detectors, also running as an AWS Lambda function, would pull the parsed data from the S3 bucket and analyze the frames and audio for any issues. Finally, the orchestration... - Source: dev.to / 12 months 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 / over 1 year 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 / almost 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
Zapier - Connect the apps you use everyday to automate your work and be more productive. 1000+ apps and easy integrations - get started in minutes.
Google BigQuery - A fully managed data warehouse for large-scale data analytics.
Nintex - Cloud-based digital workflow management automation platform
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.
AWS Lambda - Automatic, event-driven compute 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.