AWS Glue vs. AWS IoT Core vs. Toad Data Point

One of AWS Glue's most notable features that aid in the creation and transformation of data is its data catalog. Support, scheduling, and the automation of the data schema recognition make it superior to its competitors aside from that. It also integrates perfectly with other AWS tools. The main restriction may be integrated with systems outside of the AWS environment. It functions flawlessly with the current AWS services but not with other goods. Another potential restriction that comes to mind is that glue operates on a spark, which means the engineer needs to be conversant in the language.

Incentivized

End-to-end encryption is an amazing feature because we use IoT to connect to various devices in order to gather data/ stats in real-time. We're able to publish solutions with ease and at a faster rate because of AWS IoT Core. However, its inability to interact with other IoT tools is a big con that I would like them to improve upon.

Incentivized

Appropriate for general querying and some DBA work. It's the universal least-offensive solution for most environments - not best of breed, but not subject to unusual/extensive requirements. It just works. On the other hand, some functionality (e.g. data import/export, snippets) are perfunctory and minimal and seem to be either difficult or impossible to automate. If you need to streamline those operations, you'll be forced to rely on third-party solutions that mostly work on top of (instead of with) TOAD.

Incentivized

• It is extremely fast, easy, and self-intuitive. Though it is a suite of services, it requires pretty less time to get control over it.
• As it is a managed service, one need not take care of a lot of underlying details. The identification of data schema, code generation, customization, and orchestration of the different job components allows the developers to focus on the core business problem without worrying about infrastructure issues.
• It is a pay-as-you-go service. So, there is no need to provide any capacity in advance. So, it makes scheduling much easier.

Incentivized

• AWS IoT Core integrates power analytics and an AI solution for sensor data processing.
• Great protocol support including HTTPs and MQTT required to connect resource constraint IoT devices to cloud
• High security standards during data transmission
• Scalability and a great user community

Incentivized

• Export data into excel.
• Export data into excel using a pivot table functionality.
• Navigation between windows is intuitive and easy to understand.
• Good for SQL novices and experts alike.

Incentivized

• In-Stream schema registries feature people can not use this more efficiently
• in Connections feature they can add more connectors as well
• The crucial problem with AWS Glue is that it only works with AWS.

Incentivized

• Ability to integrate with Ethercalc software solution
• Ability to introduce NFC toolchains and systems which could be utilized in iot modular gateway solutions like drones
• Ability to reduce latency as the solution scales is very much needed
• Hybrid solution which can integrate other existing iot solutions into AWS iot core

Incentivized

• The workflow is a relatively new feature. Quest is adding additional functionality and the workflows are useful now.
• Would be nice if the 'Automate' feature was a bit easier to use.
• Would be nice if some of the SQL Editor features in the traditional interface worked better in the new workflow interface (although, these are being fixed with each release).
• Would be nice if there were fewer releases.

Incentivized

While easy to set up and manage monitoring for large datasets, its complexity can be a barrier for new users. Integration with AWS Ecosystem, Managed Monitoring, Dashboards and monitoring tools for AWS Glue are generally easy to set up and maintain, Automated Data Pipelines. Automates data pipeline creation, making it efficient for certain data integration

Incentivized

I give AWS IoT Core's overall usability this rating because it is very easy to use and is enjoyed by all of our staff. The only problem is that it sometimes glitches and it freezes a lot. So overall, the usability of AWS IoT Core is very good, and we will continue to use it.

Incentivized

I find Toad Data Point easy to use for both the novice and the experienced business analyst. If all you desire is to access data and create spreadsheets...this is a snap. Toad Data Point actually has cool data analysis features built into it. The newer workflow interface makes automating steps a snap

Incentivized

Amazon responds in good time once the ticket has been generated but needs to generate tickets frequent because very few sample codes are available, and it's not cover all the scenarios.

Incentivized

It covers all the aspects of IoT services required for an IoT company. It supports all the industry-wide protocols for secure data transmission and integrates powerful AL and ML technology for data analytics. For data storage, Amazon S3 is a great solution. Strong tech support and user community. Since it is widely used as compared to other products, there is an abundance of training and learning material on the web.

Incentivized

AWS Glue is a fully managed ETL service that automates many ETL tasks, making it easier to set AWS Glue simplifies ETL through a visual interface and automated code generation.

Azure IoT service provides more or less the same services as compared to AWS IoT core, however the costing of AWS lead us to continued usage of IoT core over Azure IoT services. Also, considering our existing technology stack is on AWS, it was a natural selection for better integration and ease of use.

Incentivized

Although Toad and UltraEdit are both great products, from an SQL standpoint Toad is a much better editor and troubleshooter.

Incentivized

• We are using GLUE for our ETL purpose. it’s ease with other our AWS services makes our ROI, 100% ROI.
• One missing piece was compatibility with other data source for which we found a work around and made our data source as S3 only, so our dependencies on other data source is also reducing

Incentivized

• Gives confidence to prototype iot solutions across lots of devices in little time
• Ability to meet requirements for managing a variety of communication protocols
• Learning iot analytics and visualization for faster insights enablement
• Onboarding devices and managing quickly without building inhouse solutions

Incentivized

• It is the least common denominator - not particularly optimized for our environment or workflows.
• Hangs or slowdowns add anywhere from 5% - 7% for projects utilizing large/complicated data setts. (This could be due to other IT-imposed constraints and not entirely due to TOAD.)
• Trying to perform some operations requires reading documentation and experimenting in order to figure out the TOAD-specific approaches and commands.
• It just works (when we understand it). Updates don't break things and things don't suddenly start behaving differently. Best of all, we don't mysteriously lose functionality.

Incentivized