

Find out what your peers are saying about Amazon Web Services (AWS), Informatica, Palantir and others in Cloud Data Integration.
That cut down our pipeline maintenance and integration overhead by eighty to ninety percent, freeing us up to focus entirely on actual data analysis and building user-facing features.
Previously it took me about a month to a month and a half to have a prototype of roughly five to ten screens. Now I can do it in about two to three days.
We've got a project at the moment that we estimated the integration was going to be around $200,000 to $300,000, and we've been able to achieve the integration for less than a tenth of that, doing it in-house using Stitch.
There is a clear return on investment because there is a significant amount of time saved and productivity gained, with roughly 30% to 50% of the time being reduced in solving production tickets heavily dependent on ad-hoc queries and accessing data from multiple sources.
If they contain duplicate counts or null records or improper data, those records would not be reliable.
Tasks such as querying data, validating results, and troubleshooting database issues became more efficient, which helped save time during development and testing.
The best skill set they've got is that they know when the issue is outside of their knowledge, and they escalate really quickly so that we get to the right people when we need them.
The platform actually has a very clear interface and a very good user experience.
The quality of their support is excellent, and the speed is very good, too.
They resolved my issue within a day which was specifically around licensing.
Overall, the service is excellent.
I would advise that you should not use Stitch if you are going to build a big number of screens or a heavy UI application with complex designs because it is not ready for that kind of work.
We just spin up a new server and add it into a cluster, and then it pretty much manages the load balancing across all the servers in the cluster.
If you are using the cloud version, then definitely it is scalable for sure.
It does not scale well when considering the high cost of the Mac license.
Some aspects, like scalability, could be improved to avoid writing different codes for each database.
Scalability has not been an issue because so far we have dumped about a billion records per year, and I do not see any issues as such.
Stitch is really stable.
I have not run into any major platform downtime or critical bugs that disrupted our data flow.
I didn't notice any explicit crashes or bugs with Stitch, as it is actually stable.
Toad Data Point has been stable overall in my experience, especially for regular database querying and daily development tasks.
Most of the time, it performed consistently when running queries, connecting to data sources, and analyzing data.
I often feel instability locally because it is a heavy application, and I feel some slowness in the response of the user interface.
Stitch cannot connect to all databases or third-party apps, such as Amazon Seller.
I saved a lot of time getting from having no design inspiration to having full-fledged designs.
I suggest developing a featured interface that is easier to use.
Better data visualization tools, improved integrations with modern tools, and enhanced collaboration features such as shared query libraries and real-time collaborations would be beneficial.
Toad Data Point should include more features for utilizing AI, which can automatically perform many tasks.
The application is heavy on my local PC; however, if I connect to a remote server, I think it works better.
My experience with pricing, setup cost, and licensing is that it is pretty easy, pretty straightforward, and the cheapest of them all.
The cost of the seats is actually cheaper by the amount of value that you're adding to the business.
If you are using any ETL tool, they are too expensive.
The Mac licenses are expensive, costing 1,600 dollars each.
The pricing for Toad Data Point is where it gets into trouble.
The pricing is cost-effective; it is neither too cheap nor too expensive, it's a good value.
The image to HTML conversion helps me in my projects because it allows you to acquire professional designs without starting from scratch.
We take one week of time to design an application, but now we can design that application within two days, which is 16 hours.
We can easily move and do time-to-market for a new pipeline and new integration, positively impacting our organization.
I am able to have cross-connection queries, blend and join data from multiple different databases in a single query, with data profiling, automation and scheduling, and export and reporting tools.
I utilize automations in my database with Ansible automations, performing automation data processing units and deployment, which has a positive impact, increasing efficiency and reducing human error, as well as saving time, thus improving productivity and scalability compared to human errors.
Broad connectivity with the visual query builder because it is the most valuable for me as I can connect to different data sources, build queries quickly with drag-and-drop, and validate the results without writing everything manually from scratch.


| Company Size | Count |
|---|---|
| Small Business | 6 |
| Midsize Enterprise | 3 |
| Large Enterprise | 5 |
| Company Size | Count |
|---|---|
| Small Business | 2 |
| Midsize Enterprise | 1 |
| Large Enterprise | 11 |
Stitch is a cloud-based ETL service designed to synchronize data between a variety of sources and destinations, offering robust and scalable data integration capabilities.
Stitch facilitates seamless data integration, providing users with real-time data movement across their tech stack. Its flexible architecture allows easy connectivity between diverse systems and ensures data consistency. With its user-friendly setup, Stitch empowers data teams to efficiently manage complex data workflows, enhancing decision-making and operational efficiency.
What are Stitch's most important features?In industries like e-commerce and finance, Stitch is instrumental in integrating data from sales platforms and financial systems to analytics tools. Retailers can combine online and offline sales data, while financial firms streamline data into centralized repositories, ensuring comprehensive analysis and reporting.
Toad Data Point offers a user-friendly platform for streamlined database management, providing effective tools for data integration and analysis across multiple databases.
With a focus on enhancing database management efficiency, Toad Data Point facilitates smooth SQL querying and data preparation for organizations. Its seamless integration with different databases like Oracle, DB2, and MySQL allows for effective data analysis and workflow automation. Users benefit from drag-and-drop query building and AI-assisted analysis, enhancing productivity while enabling data-driven decision-making.
What are the key features of Toad Data Point?In industries requiring extensive data analysis and reporting, Toad Data Point is deployed to streamline operations. Businesses engage it for SQL queries, data preparation, and cross-database analysis, which are critical for sectors reliant on accurate data and timely insights.
We monitor all Cloud Data Integration reviews to prevent fraudulent reviews and keep review quality high. We do not post reviews by company employees or direct competitors. We validate each review for authenticity via cross-reference with LinkedIn, and personal follow-up with the reviewer when necessary.