Jupyter
Looker
Databricks
Google BigQuery
Presto DB
Rakam
Informatica
Concurrent
DynamoDB
AWS Lambda
MongoDB
Redis
Amazon S3
MySQL
Apache Cassandra
Amazon API Gateway
Jupyter DynamoDBBased on our record, Jupyter should be more popular than DynamoDB. It has been mentiond 205 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.
JupyterLab: JupyterLab is an interactive development environment that allows you to create and share documents containing live code, equations, visualizations, and narrative text. It's particularly well-suited for data science and research-oriented projects. - Source: dev.to / 21 days ago
Jupyter Lab web-based interactive development environment. - Source: dev.to / about 1 month ago
Choosing IDE: Selecting a suitable Integrated Development Environment (IDE) is crucial for efficient coding. Consider popular options such as PyCharm, Visual Studio Code, or Jupyter Notebook. Install your preferred IDE and ensure it's configured to work with Python. - Source: dev.to / 27 days ago
Jupyter Notebooks is very popular among data people specially Python users. So, I tried to find a way to run the Groovy kernel inside a Jupyter Notebook, and to my surprise, I found a way, BeakerX! - Source: dev.to / 2 months ago
Note. Nowadays, there are many flavors of notebooks (Jupyter, VSCode, Databricks, etc.), but they’re all built on top of IPython. Therefore, the Magics developed should be reusable across environments. - Source: dev.to / 2 months ago
DynamoDB is a powerful NoSQL database provided by AWS, designed to handle large amounts of data efficiently. However, for newcomers, understanding the nuances of querying DynamoDB tables can be challenging, particularly when it comes to the differences between KeyConditionExpression and FilterExpression. This blog post aims to clarify these concepts and provide practical examples of their usage. - Source: dev.to / about 4 hours ago
Event Producers: Generate streams of events, which can be implemented using straightforward microservices with AWS Lambda (for serverless computing), Amazon DynamoDB Streams (to captures changes to DynamoDB tables in real-time), Amazon S3 Event Notifications (Notify when certain events occur in S3 buckets) or AWS Fargate (a serverless compute engine for containers). - Source: dev.to / 17 days ago
The first is AWS DynamoDB which is going to act as our NoSQL database for our project which we’re also going to pair with a Single-Table design architecture. - Source: dev.to / 15 days ago
DynamoDB - 25GB NoSQL DB EC2 - 750 hours per month of t2.micro or t3.micro(12mo). 100GB egress per month. - Source: dev.to / 3 months ago
After two years, I moved to a Web3 startup where I was given a lead software engineer role. This new role gave me more hands-on experience with AWS, where I've learned to implement serverless technologies like Lambda and DynamoDB. - Source: dev.to / 5 months ago
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
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.
Google BigQuery - A fully managed data warehouse for large-scale data analytics.
Redis - Redis is an open source in-memory data structure project implementing a distributed, in-memory key-value database with optional durability.
