Amazon S3 Reviews

The primary use case of this solution is for storage.

The most valuable features are unlimited storage, scalability, and performance.

The security model can be improved as it is a bit confusing.

The access speed could be faster.

I have been familiar with Amazon S3 for six years now.

I am always using the latest version because it is self-service, and you cannot choose the version you are using.

It's a stable solution.

It's a scalable solution.

I provide consulting services for this product and every customer we have is using it. Our clients are enterprise businesses.

I have used Amazon support for this product and I find the service to be good. We also try to provide for our clients.

The initial setup is easy, it's straightforward, and it only takes a few minutes to deploy.

I have experience with many cloud services and with several services through Amazon.

I would recommend this solution.

I would rate this solution a nine out of ten.

We use this solution to store the historical data of the customer. Additionally, we are creating JSON format data while running our application and we are pushing this JSON format data to the Amazon S3.

This solution is good at storing historical data and we were using it for other purposes.

When we need to find the queries there is no user interface, it is the only textual format that is bulky. If we need some data we will use Athena for queries and we will get results. When comparing this solution to others, such as DataDog, they provide a wonderful UI, and user-friendly dashboards, and many other features that this solution is lacking.

We have found that the query takes too much time to process and it is quite difficult to receive the data.

I have been using the solution for approximately three years.

The solution is stable.

I have found the solution scalable.

The initial setup was quite complex. We needed to create some endpoints but with a little effort everything turned out alright. Additionally, we use Kafka queues and we send them to the S3 bucket. With the help of shell scripts, we run one script and we receive the data from Kafka queue, topic by topic, and we send the data to the S3 bucket.

The cost of storage is cheap. However, the cost to have a better interface can get expensive. We are using Athena for this purpose and if we did some heavy queries the cost will start adding up. When the Athena query is running, it will scan the bucket and they charge for how many GBs we are going to scan. The function of scanning has a lot of costs attached to it, this is a negative point.

I have evaluated Datadog and Kibana and we are planning on moving away from Amazon S3 and S3 Athena because the other solutions provide the latest technology.

We should not use this solution for the purpose of the logs. We realized if we need to track the logs and a few other things we should use a good log platform which would have been better.

We plan to keep using this solution in the future but only for a specific set of purposes. We are moving away from S3 to a different solution, such as Datadog or Elasticsearch because 80% of the usage is only for storage purposes. We will keep on doing the same thing in the future. Only 20% of our usage we are planning to move from S3 to a log platform.

I would advise others if this solution fits the use case or expected usage for the end-user then I would recommend it. If they can afford everything that is involved, such as storage and usage fees, then it would be a good choice. They have to consider how frequently they want to access the data from the storage, how many heavy queries they want to run, and are they going to manipulate the data or retrieve the data. They should consider all these scenarios before they make the decision to implement the solution.

I rate Amazon S3an eight out of ten.

Speed, size, and security are the most valuable features.

This was the company’s first foray into storing data offsite. The old way of thinking was that this was too dangerous to contemplate and you can get hacked either way.

This solution, indirectly, allowed us to recover internal and expensive document storage and replace it with cheaper offline storage.

Capacity-wise, we’re looking at 200GB of transactional data in Redshift. More importantly, you have a lot of storage of other assets, some slow and some fast. These include document archives and web images. This is several years of documents of more than 500GB, and most of it will remain untouched.

That stuff ends up in S3 Glacier storage. It is not really that large in the grand scheme of things, but certainly does not warrant the use of expensive internal storage systems or hiding the data on backup tape somewhere.

The web interface was frustrating when dealing with large numbers of files. We ended up using an interface client (via FTP, I think) which also had its own issues.

How do you make it easy to manage 50K documents in one folder using a web interface? I guess some more advanced filtering and selecting capabilities would have been nice, but it was in the early days. It would only read about 120 files into the cache. If you wanted to remove 1000 out of 2000 documents, you had to continually repeat your actions.

This happened surprisingly regularly when you have a live data transfer that ships 100 files per cycle and does 20 cycles per hour. It could eventually delete them itself, but we didn’t have time to engineer that piece.

Amazon’s approach was to delete the old files after a certain number of days. That is money in the bank for them right there.

I have used this solution for three years.

There were no stability issues.

Technical support always met my expectations.

There were business intelligence solutions via the web. We had similar home-grown reporting applications running on in-house hardware for over 10 years prior, but this was directly impacting our ERP resources.

It was exceptionally simple to configure servers, although most of this was done by the boss.

Even though it appears cheap, be careful on how you use it. Optimizing early will save money spent on storage and resources long term, so make it part of the design process. The beauty is you can control it at a very fine level.

Follow the guidance. The documentation is excellent. Take the time to get it right.