Amazon Cognito
Auth0
Okta
OneLogin
Microsoft Azure Active Directory
Ping Identity
Atlassian Crowd
Google Cloud IAM
Amazon EMR
Google BigQuery
Google Cloud Dataflow
Google Cloud Dataproc
Databricks
Qubole
Snowflake
HortonWorks Data Platform
Amazon Cognito Amazon EMRBased on our record, Amazon Cognito should be more popular than Amazon EMR. It has been mentiond 65 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.
The authentication system is web based and thus uses HTML1. There is a backend written in JavaScript (actually TypeScript), which in turn - for some operations - talks to a service written in .NET that stores data in AWS Cognito. - Source: dev.to / 9 days ago
While we highly suggest shifting to OIDC, companies that cannot shift away from SAML can find an OIDC compliant federating identity provider (such as Amazon Cognito) to implement SSO through Pomerium and save on the SSO tax. - Source: dev.to / 16 days ago
I’ve heard some people complain about AWS Cognito’s complexity, but I’ve had the opposite experience. I’ve never done on-boarding before, and every project I’ve ever been on, or near, on-boarding was always a horror show, both in UI, ability to debug, and stability. - Source: dev.to / 3 months ago
After setting up an Amplify app, the next step is to add authentication to the project. Writing the logic for an application's login flow can be challenging and time-consuming. You are responsible for handling tokens correctly, managing user sessions, and storaing user details. However, Amplify simplifies this process by providing a complete authentication solution, which uses Amazon Cognito under the hood, that... - Source: dev.to / 5 months ago
Building auth for your SaaS product shouldn't be hard. Try these free solutions for your next project 👇 Http://supabase.com/auth Free up to 50k users/month Http://firebase.google.com/products/auth Free up to 50k users/month Http://aws.amazon.com/cognito Free up to 50k users/month Http://clerk.com Free up to 10k users/month Http://kinde.com Free up to 7.5k users/month Https://www.descope.com Free up to... Source: 6 months ago
There are different ways to implement parallel dataflows, such as using parallel data processing frameworks like Apache Hadoop, Apache Spark, and Apache Flink, or using cloud-based services like Amazon EMR and Google Cloud Dataflow. It is also possible to use parallel dataflow frameworks to handle big data and distributed computing, like Apache Nifi and Apache Kafka. Source: over 1 year ago
I'm going to guess you want something like EMR. Which can take large data sets segment it across multiple executors and coalesce the data back into a final dataset. Source: almost 2 years ago
This is exactly the kind of workload EMR was made for, you can even run it serverless nowadays. Athena might be a viable option as well. Source: about 2 years ago
Apache Spark is one of the most actively developed open-source projects in big data. The following code examples require that you have Spark set up and can execute Python code using the PySpark library. The examples also require that you have your data in Amazon S3 (Simple Storage Service). All this is set up on AWS EMR (Elastic MapReduce). - Source: dev.to / over 2 years ago
Check out https://aws.amazon.com/emr/. Source: about 2 years ago
Auth0 - Auth0 is a program for people to get authentication and authorization services for their own business use.
Google BigQuery - A fully managed data warehouse for large-scale data analytics.
Okta - Enterprise-grade identity management for all your apps, users & devices
Google Cloud Dataflow - Google Cloud Dataflow is a fully-managed cloud service and programming model for batch and streaming big data processing.
OneLogin - On-demand SSO, directory integration, user provisioning and more
Google Cloud Dataproc - Managed Apache Spark and Apache Hadoop service which is fast, easy to use, and low cost
