Spring Security
OpenSSL
Let's Encrypt
Ensighten
Auth0
Firebase Authentication
Amazon Cognito
Keycloak
Amazon EMR
Google BigQuery
Google Cloud Dataflow
Google Cloud Dataproc
Databricks
Qubole
Snowflake
HortonWorks Data Platform
Spring Security Amazon EMRAmazon EMR might be a bit more popular than Spring Security. We know about 10 links to it since March 2021 and only 8 links to Spring Security. 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.
Website: https://spring.io/projects/spring-security. Source: about 1 year ago
Https://spring.io/projects/spring-security Open source authN and authZ framework for Spring (Java). - Source: dev.to / over 1 year ago
Start reading here: https://spring.io/projects/spring-security Basically you have a spring security config which defines a filter chain. There you can also define the filtering for any endpoint of your server. Source: over 1 year ago
The official documentation of spring is : spring.io? In this case (spring security) : https://spring.io/projects/spring-security ? Source: almost 2 years ago
Disclosure: I work for FusionAuth. Depends on what you are looking for. If you want a standalone auth server, you can use FusionAuth in docker/docker-compose: https://fusionauth.io/docs/v1/tech/installation-guide/docker You can also package up a library; most major languages have one or more OAuth/OIDC libraries: https://github.com/doorkeeper-gem/doorkeeper for Ruby, https://spring.io/projects/spring-security for... - Source: Hacker News / about 2 years 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
OpenSSL - OpenSSL is a free and open source software cryptography library that implements both the Secure Sockets Layer (SSL) and the Transport Layer Security (TLS) protocols, which are primarily used to provide secure communications between web browsers and …
Google BigQuery - A fully managed data warehouse for large-scale data analytics.
Let's Encrypt - Let’s Encrypt is a free, automated, and open certificate authority brought to you by the Internet Security Research Group (ISRG).
Google Cloud Dataflow - Google Cloud Dataflow is a fully-managed cloud service and programming model for batch and streaming big data processing.
Ensighten - Ensighten provides enterprise tag management solutions that enable businesses manage their websites more effectively.
Google Cloud Dataproc - Managed Apache Spark and Apache Hadoop service which is fast, easy to use, and low cost
