What is Amazon S3?
What is Heroku Redis?
Need advice about which tool to choose?Ask the StackShare community!
Sign up to add, upvote and see more prosMake informed product decisions
Sign up to get full access to all the companiesMake informed product decisions
Sign up to get full access to all the tool integrationsMake informed product decisions
Insanely low prices, quite easy to use, and they're fast. Plus they provide great support. And they're integrated with other AWS services, like CloudFront.
Seriously, this is the best service of it's kind out there.
Used MongoDB as primary database. It holds trip data of NYC taxis for the year 2013. It is a huge dataset and it's primary feature is geo coordinates with pickup and drop off locations. Also used MongoDB's map reduce to process this large dataset for aggregation. This aggregated result was then used to show visualizations.
MongoDB fills our more traditional database needs. We knew we wanted Trello to be blisteringly fast. One of the coolest and most performance-obsessed teams we know is our next-door neighbor and sister company StackExchange. Talking to their dev lead David at lunch one day, I learned that even though they use SQL Server for data storage, they actually primarily store a lot of their data in a denormalized format for performance, and normalize only when they need to.
We store the software components that CloudRepo stores for its customers here for the following reasons:
- Data is Encrypted at Rest
- Data is stored across multiple physical locations
- Pricing is competitive
- Reliability is industry leading and our customers need to be able to access their data at all times list text here
Nearly all of our backend storage is on MongoDB. This has also worked out pretty well. It's enabled us to scale up faster/easier than if we had rolled our own solution on top of PostgreSQL (which we were using previously). There have been a few roadbumps along the way, but the team at 10gen has been a big help with thing.
In October 2008 we moved to using scribe (now a custom branch), which has served us very well over the past 5+ years that we’ve been using it. We take the logs scribe aggregates and move them into Amazon S3 for storage, which makes using EMR on AWS seamless.
S3 serves as zero-knowledge temporary storage. Files are encrypted in the browser before being uploaded in chunks to S3. When the target recipient downloads them the chunks are reassembled and decrypted in the browser. Files expire after a week and the encrypted chunks are permanently deleted from S3.
We are testing out MongoDB at the moment. Currently we are only using a small EC2 setup for a delayed job queue backed by
agenda. If it works out well we might look to see where it could become a primary document storage engine for us.
Used for proofs of concept and personal projects with a document data model, especially with need for strong geographic queries. Often not chosen in long term apps due to chance data model can end up relational as needs develop.
Since we generate a static website for our website, AWS S3 provides hosting for us so that we don't have to run our own servers just to serve up static content.
The pricing is great as you only pay for what you use.
This object storage is always evolving and getting harder to explain. We use it for 1) hosting every static websites, 2) datalake to store every transaction and 3) query with Athena / S3 Select.