AWS Data Exchange vs. Dataloader.io

AWS Data Exchange fits best for scenarios where you have datasets that you would like to sell and you want to deliver it to anyone who would like to purchase it. It really beats having to set up downloads via your own website or portal. However, it can get complicated to manage if you're trying to deliver a dataset a client has already paid for.

Incentivized

Replacing data. If we've put something in a category or a bucket that is no longer named that anymore because we've evolved with the times and we want to rebrand everything, it makes it way easier to do a quick import with the new terms.

Incentivized

• Simplified data delivery
• Ability to create any amount of data products
• Ability to integrate payment plans with data products
• Tracking data downloads and users
• Integration with other AWS data services

Incentivized

• Extracting Salesforce attachments in original file format! I do not know of a tool that can do this better, or more efficiently! This is a huge benefit to companies that would like to extract attachments from Salesforce for tasks like data migrations.
• Cross-object data extract within one file. You can pull data from related objects as long as there is a populated lookup from the object you are extracting, to another object (Child or Parent).
• UI is simple and requires very little to no training. Given the acquisition of Mulesoft by Salesforce, I would not be surprised if DataLoader.IO is rolled out as the new global data loading tool for Salesforce.

Incentivized

• Integration with more data sources
• Ability to deliver data to clients without AWS accounts
• Inclusion of direct data downloads in addition to asynchronous methods

Incentivized

• At the moment, I can't find a way to rename jobs. This would be useful to organize what was previously created hastily by techs in a rush.
• A preview of the job, especially upserts, would take a great deal of stress away from some of us (especially those who are not so confident in their ETL practice).
• A native vlookup equivalent may be a welcome addition.

There have been a lot of problems with ADX. First, the entire system is incredibly clunky from beginning to end.First, by AWS's own admission they're missing a lot of "tablestakes functionality" like the ability to see who is coming to your pages, more flexibility to edit and update your listings, the ability to create a storefront or catalog that actually tries to sell your products. All-in-all you're flying completely blind with AWS. In our convos with other sellers we strongly believe very little organic traffic is flowing through the AWS exchange. For the headache, it's not worth the time or the effort. It's very difficult to market or sell your products.We've also had a number of simple UX bugs where they just don't accurately reflect the attributes of your product. For instance for an S3 bucket they had "+metered costs" displayed to one of our buyers in the price. This of course caused a lot of confusion. They also misrepresented the historical revisions that were available in our product sets because of another UX bug. It's difficult to know what other things in the UX are also broken and incongruent.We also did have a purchase, but the seller is completely at their whim at providing you fake emails, fake company names, fake use cases because AWS hasn't thought through simple workflows like "why even have subscription confirmation if I can fake literally everything about a subscription request." So as a result we're now in an endless, timewasting, unhelpful thread with AWS support trying to get payment. They're confused of what to do and we feel completely lost.Lastly, the AWS team has been abysmal in addressing our concerns. Conversations with them result in a laundry list of excuses of why simple functionalities are so hard (including just having accurate documentation). It was a very frustrating and unproductive call. Our objective of our call was to help us see that ADX is a well-resourced and well-visioned product. Ultimately they couldn't clearly articulate who they built the exchange for both on the seller side and the buyer side.Don't waste your time. This is at best a very foggy experiment. Look at other sellers, they have a lot of free pages to try to get attention, but then have smart tactics to divert transactions away from the ADX. Ultimately, smart move. Why give 8-10% of your cut to a product that is basically bare-bones infrastructure.

It is easy to use and doesn't require a security token, so I enjoy using it. It also doesn't require any download or installation, which is sometimes a blocker to gettingthings done if the company has limits. also, the dataloader.io is easy for other people to pick up, so others can have visibility into the data jobs that have occurred

Dataloader definitely skews towards a more technical userbase. Users should be adept at manipulating data in spreadsheets and decipher JSON formatted error messaging. Additionally, there is a good amount of time need to set up the environment to map to the pertinent fields we are trying to adjust. While I would not recommend the typical account manager to use Dataloader, a typical operations manager should have no issue.

Incentivized

Dataloader is made for updating, inserting, and deleting of contacts. For these operations this tool is excellent.

Incentivized

The utility itself is very self-explanatory and has enough information to guide you through the process. It has an intuitive experience for those familiar with data loading/exporting utilities. Outside of this, they have a Zendesk help center to log support requests and provide documentation to help guide you troubleshoot any issues that may be occurring.

Incentivized

I have used salesforce inspector also for operations like import and export of data from custom objects but it doesn't work well when you have data in huge numbers. Instead of using Salesforce Inspector, one should go for Dataloader.io if the number of records is huge to be dealt with.

Incentivized

• Reduced time to publish datasets for sale by more than 80%
• Increased net profit from dataset sales by ~10%
• Reduced data delivery time to clients by 15%

Incentivized

• HUGE time saving. When we need to clean or review data, we used to have to do it line by line. This can do the work within excel and make cleanup/management an afternoons work as opposed to a week.
• Rollback what you did/change/deleted is relatively simple if you remember to back up the data you are manipulating.

Incentivized