Cloud Firestore VS Amazon EMR

Firebase is an app development platform backed by Google that famously replaces the need for a backend. It accomplishes this by providing developers with a variety of services, including authentication, push notifications, and a database called Cloud Firestore that can be adapted to store and broadcast chat messages in realtime. - Source: dev.to / 3 months ago

Within the Firebase system, I use Firestore. To minimize queries of multiple collections ( keep server costs down ) I keep users in one collection. Within each user object I have a "roles" property that is a sub-object referencing the different roles available:. Source: 5 months ago

NoSQL is a term that we have become very familiar with in recent times and it is used to describe a set of databases that don't make use of SQL when writing & composing queries. There are loads of different types of NoSQL databases ranging from key-value databases like the Reddis to document-oriented databases like MongoDB and Firestore to graph databases like Neo4J to multi-paradigm databases like FaunaDB and... - Source: dev.to / 8 months ago

Oh, I don't think this is what you're looking for. It's NoSQL versus Supabase's PostgreSQL implementation. {sigh}. Source: 10 months ago

I tried to make a reddit like app. I used both realtime-database and firestore as database. The billing of the two is different from each other. I used realtime-database for frequently updated data (like or upvote, downvote count for ex.) and firestore for more stable and large data (post, comment, community and user data..). While doing this, I only used database rules, I did not use Cloud functions. So, I... Source: 11 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: about 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: almost 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