Stitch Reviews

Stitch is primarily used for integration between multiple systems in our environment. On top of that, we have data integration and data analysis. We draw information from multiple systems, both systems that we manage ourselves, and we have a number of data partners that manage their data. We hook into their environments, use their information and our information, mix it all up, and then develop new products. Primarily, we're using it for analysis around the data that's captured around the environment. Our council is responsible for looking after a large chunk of New Zealand and monitoring air and water and sea, and managing the quality of a large number of different environmental factors. We need to keep reporting that in real-time aggregation on a monthly and yearly basis. We're looking at how climate change is affecting our environment and reporting on anything about the environment.

The benefits of Stitch that we see are the ease of being able to integrate and visualize data that's in other systems. We're dealing with APIs, both XML and JSON, and pretty much every integration format that you can imagine. The platform itself is really easy to hook into all of those different outside sources and bring it in and transform it into a format that meets all of our internal systems. It's just the ease of use really.

We're connecting to everything with the extensive connector library in Stitch. There are pre-built connectors already in there, but one of the big powerful things about Stitch is that a lot of these specialized systems aren't standard connectors, like SAP or any of those big systems. Because the components themselves are very configurable, we can actually connect to systems that don't have a standard interface connection or have an API but the XML format isn't quite normal or the JSON format isn't quite normal or whatever format they're in. Stitch allows us to connect to those specialized data sources and transform them into a format that's easy for us to deal with internally.

The transformation language feature helps with data consistency in our case, as we convert everything into JSON. JSON is our internal standard for data formats. Stitch makes that whole data transformation part really easy. That was the biggest selling point for us.

The schema evolution capability helps to maintain data integrity because a lot of these systems don't change, but when they do change, we need to be able to manage that change in a controlled manner. The ability to transform based on different versions is where Stitch is really powerful. We can set up version one using a transformation standard, but when we upgrade to version two, it transforms the whole mapping capability. It makes it really easy to go from version one to version two in real-time. We don't have to convert the whole database; we can transform it as we need it, which means that we don't have to go through a big migration anytime there's an upgrade or change from the source system.

One of the key things is that we need benefits from real-time insights and monitoring tools in the product because we need to know when something goes wrong or something isn't part of the standard pattern. The jobs themselves alert us when something goes a little bit differently or doesn't fit the existing pattern. It doesn't stop the whole job, but it gives us an alert and makes us aware of what's actually going on so that we can intervene if we actually need to. But a lot of the time it's more of an information notification about what has changed rather than a critical alert. However, over time, those little variations do grow and grow, and the platform allows us to actually keep track of how far things are actually growing or changing so that we can then interpret whether it's the best time to actually make a change to the whole program of work, or whether we can just live with it for a bit longer.

The automation features in the product have a significant impact on our data management process because we would not be able to do what we currently do if we didn't automate. The number of data sources that we're dealing with is growing, and every year there's probably twice as many as there were the previous year. We've only got a small team, so by automating, we don't have to spend a lot of time building new internal resources to manage it. We've pretty much got the same size team as we did four years ago. The automation just makes our lives really easy.

The best thing that we've seen coming out of Stitch is the Talend and Qlik relationship becoming more of a single entity rather than two entities. A couple of years ago there was a distinction between Stitch and Qlik. The biggest challenge when we were dealing with both was that we felt like we were dealing with two different companies. They are quickly merging the two different entities into a single one, and by around the end of this year, they're planning to basically consolidate everything. Until then, it does get a little bit complicated when we have Qlik and Stitch components together. It's not quite exactly one solution. That's probably the biggest negative at the moment. Each month we're seeing improvements in the cloud platform, and they're coming out with capabilities that we haven't even thought about that are going to make our lives easier. Probably the biggest negative they have is they're doing so much good stuff, but we don't know about it. It just appears and then we figure it out ourselves, but the communication of changes could be improved. However, the positives are that they're changing so much at the moment.

We've been using Stitch for about three or four years now.

The only real glitches we've experienced with Stitch are when we have uncontrolled change in our environment. All environments are reliant on their firewalls and networks. If we don't change anything to do with the firewall settings, then the last time we had a server issue was probably around seven or eight months ago. It's all running in a cluster, and we can auto-restart servers whenever we feel appropriate for load balancing or the distribution of job resources. Stitch is really stable.

We've found that the scalability of Stitch is really easy. The easiest part is that 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. We keep track of how much CPU is being used at different peak times and all of that. Because we manage most of the load ourselves internally and it's based on internal systems, we're actually pulling more data into our environment and feeding it out to external customers. We can control that load quite well. When it does hit the limits, we just add a new server into the mix and let Stitch manage itself. It seems to work really effectively.

The initial support people from Qlik are really good. 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. We've got a couple of solutions internally that seem a little bit unnecessary, where we ask a question of the support desk and they'll spend a week or two trying to resolve the issue when they really don't have the technical know-how. That's one of the really good things with Stitch support. If they don't know it, they escalate it and we get somebody who can resolve the issue really quickly. The support people are excellent.

Positive

The deploying and initial setup of the product is straightforward, but there's a little bit of configuration involved with the remote engines and the runtime environment. The documentation is really good. You quite literally just follow the steps that they say and then double-click an executable and you're away. We have had a couple of issues and they've primarily been our problem rather than the Stitch environment. When we've done upgrades and haven't kept up with the regular monthly updates, we've had things get out of sync. We've had to reinstall the Studio type environment, and it was a complete mess. However, twenty minutes later, we reinstalled it and everything was completely up and running with no problems at all.

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. Additionally, long-term, the support and maintenance are better because we don't have to manage bespoke code and we don't have to manage the life cycle around that code. It's all built inside of Stitch and managed for us. It's quite literally a configuration rather than a writing code scenario. We've done a huge saving and that's only one of a number of projects that we've got on where the same sort of things are happening.

The worst thing about the price and licensing model of the product is that it sounds really expensive when you start to go into it because a lot of systems require ten or twelve seats. The challenge with Stitch and the whole Qlik environment is that you don't need ten seats, you just need three or four. The three or four seats will actually do the same as what you would have ten or twelve people in another system. People look at the price of the seats and think it's really expensive and that they're going to have to put ten or twelve people onto it. Actually, if you put ten or twelve people onto it, they'll be running out of work pretty quick because you'll be able to achieve so much more faster and don't need quite as big a team. The cost of the seats is actually cheaper by the amount of value that you're adding to the business. The seats sound expensive, but long-term, they're probably a lot more cost-effective for the amount of volume of work that you're getting through and the value you're adding to the business.

Stitch is definitely worth going for. A little bit hard to provide some metrics or examples of the impact on the data management process, but we have seen the number of transactions per minute increase by about 400 to 500 percent in the last two years. The number of meters that we have out in the real world actually measuring things like air quality and water flow has increased by about 300 percent. The number of databases that we've connected to has probably increased about four times from what we had about three years ago. Everything is pretty much three times as much now as what it was a couple of years ago. Our overall rating for Stitch is nine out of ten.

My main use case for Stitch is to integrate retail data and connect different sources seamlessly. I mostly use it for moving data into a central warehouse, so I can easily analyze and build visualization dashboards without worrying about manual pipelines.

A specific example where I used Stitch for integrating retail data involves a project with a scrap pickup and recycling service. We had user orders coming from a web app database and offline transactional data scattered across different spreadsheets. Stitch saved us a ton of time by automatically consolidating all that retail and transactional data directly into the warehouse. It made it super easy for us to track active orders and analyze patterns without doing any manual data dumping.

Regarding my main use case for Stitch, the most unexpected thing was how easily it handles sudden spikes in data volume. When our order traffic jumped out of nowhere, I thought the pipeline might lag or drop rows, but it scaled perfectly without any manual tweaking. It completely saved me from spending a weekend troubleshooting broken schemas or API connections.

The best features Stitch offers stand out to me primarily due to its massive library of pre-built integrations and how it automatically handles schema changes. You just plug in your data sources and if a database table structure changes on the source side, Stitch automatically detects it and updates the destination warehouse. It keeps things completely hands-off, and that feature really stands out for me.

Stitch's automatic schema change detection has benefited my workflow by being a massive time-saver. Normally, if someone modifies a database column or adds a new file on the backend, the whole data pipeline would break and you would have to manually rewrite the schema mapping. With Stitch, it just adapts on the fly and logs the changes without breaking. It keeps our dashboards updated automatically.

Stitch has positively impacted my work by completely eliminating manual data entry and custom script writing for our pipeline. By automating the data flow, we drastically reduce human errors. We could focus entirely on analyzing the data rather than fixing broken data pipelines.

After using Stitch, I saved a massive amount of time. We saw a difference right away. Before using it, we were spending easily ten to fifteen hours every week just writing custom API scripts and maintaining ETL pipelines and manually cleaning up broken data formats. After setting up Stitch, that pipeline maintenance dropped down to practically zero. It cut our data integration and engineering workload by at least eighty to ninety percent, allowing us to get data into our dashboards in real-time instead of waiting days for manual updates.

If there is something Stitch can improve, I would say it is the pricing structure. It scales based on row count, so if we suddenly have a massive surge in data, our cost can jump up pretty fast. While it is great for straightforward replication, I wish it had a slightly more flexible and built-in transformation tool. Their documentation is solid and straightforward with clear setup guides for almost every major connector, making onboarding pretty painless. However, if you run into a weird edge case and need to contact their actual support team, responses can sometimes take a bit of time if you are on a standard tier. It is definitely a platform where you rely on their written docs first. Fortunately, the docs usually cover what you need.

I have been using Stitch for the last one year.

In my experience, Stitch has been incredibly stable over the past year. I have not run into any major platform downtime or critical bugs that disrupted our data flow.

Stitch's scalability is really good. It handles data scale-ups well, and we never faced a major issue or any downtime.

Before Stitch, we were relying on custom Python scripts and cron jobs to pull data from our APIs manually.

I have definitely seen a return on investment with Stitch, primarily through engineering hours saved. Instead of hiring dedicated data engineers to manually build and batch API pipelines, we saved roughly ten to fifteen hours every week. 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.

Based on my experience, the setup cost for Stitch was practically zero, since it is a fully managed cloud tool, and the initial licensing is straightforward to get going. The real catch is the consumption-based pricing model, because it changes based on the number of rows replicated. It starts out very affordable, but if your data volumes grow or you experience sudden traffic surges, the cost can scale up pretty quickly.

Before choosing Stitch, we looked at a couple of other popular ETL and data integration tools before settling on Stitch.

Regarding Stitch's AI capabilities, the governance and security side feels pretty tight. When you are feeding data through AI-driven pipelines, you worry about a lot of things. But Stitch handles data encryption both in transit and at rest really well. It gives you role-based access controls, so it feels completely safe using their automated features without worrying about leaking any sensitive user or transactional data.

On the topic of Stitch's AI capabilities, its accuracy and reliability of output have actually been incredibly reliable. When it maps out complex data fields or suggests schema adjustments automatically, it rarely gets the call wrong, and I have not noticed any major anomalies in the replicated data. It feels trustworthy enough to let it run without constantly micro-managing it.

I would rate this review an eight out of ten.

All of these things totally depend upon your business logic. If you want to remove duplicates or you want to implement some kind of format for postal addresses, like keeping pin codes in this format, you can customize your code accordingly and then you can get consistency in the data.

Since the way everyone is moving towards AI, my suggestion will be to lean more towards natural language processing. So rather than writing proper SQL, the way Snowflake is processing or Cloudera is processing things, they should also have a chatbot or something similar where we can simply write things, it understands that particular thing and enhances that particular thing at the back end.

I do remember I used to work for geographical interfaces, where we needed most of the location information. It was a petroleum extraction client. So we needed the location and everything. For that, we used libraries that were more focused on getting the basic distance between two geographical locations and everything. Those kinds of functions, if we wanted to implement them, we used to extract that particular thing from the external libraries and use it.

Definitely. Even though you are paying a huge amount, the quality and the time it takes to process big data is definitely lesser. Things are more systematic. All transformations are connected to a pipeline. If you have implemented those things in production and there is any bug, people can easily debug things and identify where exactly the pipeline has an issue. You have easily accessible logs and notifications available. There are a variety of components which can be used to implement any of your logic.

With my current client, I am working for a client who has used Stitch. They have provided it in their environment only. I do not remember from where they have purchased it.

During the processing of transformation, sometimes we used to bring up our own logic, like removing duplicates from the data if I have checked two or three keys. Rather than picking up the one which was provided, there is not a process where, for example, if I have four duplicate keys in the record and I have checked two or three fields and ideally we want something which should also utilize the way the record came. The first record which came should not be deleted, and anything other than that should be deleted. Those kinds of functionalities are not provided. It randomly deletes whatever if it finds a duplicate. These kinds of small things, I remember when I worked, I faced challenges because I was doing a migration and my data was not matching. Then I realized these kinds of features are available in this. That is the reason, it is not the problem for Stitch, it is with other ETL tools also.

Seven to eight years.

It is very rare. I have seen and faced the issue, but it was very rare that there was a network issue, meaning some kind of thing which has broken down and we were stuck and were not able to work on that.

It depends upon if you are using the cloud version, then definitely it is scalable for sure. Or if you are using a normal legacy one, then you cannot scale it that much.

Definitely positive. The kind of support Stitch provides is good.

I used to work with Azure back then.

Anything which reduces your effort of writing code is beneficial because it will reduce your time. Efficiency is important, and since it is pre-written or reusable code which we are writing, it is going to be more efficient, definitely. If they are providing automation, then definitely it will be beneficial for any of the business or any of the domains you are working on.

To be frank enough, I will say right now that since we are not using it, they are too expensive. I will be very frank to you. If you are using any ETL tool, they are too expensive. People, if they are working on any of the databases such as Snowflake or Databricks, are trying to get involved in using their functionality even more rather than picking up this additional ETL tool and moving towards that.

Other

I have moved my role, actually. So basically right now I am into management mostly. But my projects which I am handling right now do have those things that have been handled. Greenplum I have used long back in my previous organization.

If we talk about Greenplum, I worked on that around seven to eight years back. That was a long time ago. PostgreSQL is used frequently by any project, whichever you pick up. PostgreSQL is used very frequently. That is why I mention it.

I have worked with Stitch, Alteryx, Informatica, and DataStage. There are most of the ETL tools I have worked on. I worked on Stitch for five years, two years in DataStage, and I am also certified in Informatica, which is another ETL tool. I also worked for one or two years with Alteryx, which is another ETL tool.

My whole experience is on ETL only. Even though I am doing project management right now, all my products are related to migrations and everything. They involve those ETL things. Since everyone is moving towards Snowflake or Databricks, they are migrating, but the projects still use ETL tools.

I worked as a partner integrator, mostly for data transformations, extraction, and transformation. Transforming the business logics and everything.

Stitch is totally capable of doing those things. It is the way you implement it. It is totally the way you want to customize your code and you want to implement your business logic. If the developer is good enough, they can utilize that tool in a very good way.

Right now, since the way things are moving in the market, everything is on cloud right now. Mostly, even the current projects I am working on, everyone is migrating towards cloud.

The learning curve is moderate. It is not that complicated.

You need a skilled resource because what happens is the person who is a coder, such as I am a coder in Python and JavaScript, can easily go and start it. But when you are working with such kinds of tools, you need a person who is tool-specifically skilled. Have they worked on this particular tool? They need a person who has some knowledge about the tool. They should know where which functionality is available. Those kinds of details they should know.

I give this review an overall rating of eight.

I use Stitch mainly for designing and building the UI of the application and products that I was working with. I used Stitch to design and build the UI of a colony management mobile application, which stands out to me. I have used Stitch for building high-class web applications, which played a big role in my projects.

Stitch gives really better high-class mobile application UI designs that helped me with those high-class applications. Stitch gave me the option to export the HTML and CSS code for the pages it provided, which was a really good feature, even during the free trial.

For building a basic UI application structure, Stitch has been really good, and that positively impacted my organization. Stitch saved a lot of time, gave more options, and made it very quick and easy to build a UI.

Stitch only gives a few UI design pages, and not much more than that, which is an aspect that can be improved. I wish Stitch would add more screens at the same time, not a limited number, to make it even better for me. Stitch gives a very limited number of UI designs, which is what comes to mind for needed improvements.

Stitch was changing the UI design at each screen, so every screen had a different UI design that was not according to the theme of the application.

I started using Stitch when it was very new and just launched, so I have been using it from the very beginning.

I didn't notice any explicit crashes or bugs with Stitch, as it is actually stable, but still, it needs to be improved.

I think Stitch can actually handle more complex and more number of projects and complex designs because it was at a very early stage that I used it; however, I don't think that Stitch itself is scalable. 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.

Stitch's UI is actually really good, beneficial, and very beginner-friendly; however, for heavy building and highly scalable applications and a big number of screens, Stitch is not a very viable option according to me.

I never needed to contact any customer support for Stitch, and my experience with it was fine.

I haven't seen a return on investment with Stitch as it did not save me time or money.

I used Dora, which is also a very good 3D design UI artificial intelligence, before trying Stitch because it gave some free credits, although it didn't allow me to export the code. I haven't known about other options besides Dora before choosing Stitch.

I don't have any knowledge about Stitch training, but I have basically used Stitch for its free trial. I used it just two or three times for building high-end designs. The first stage with Stitch was bad due to its features.

I used the free version of Stitch, and that was all regarding its deployment in my organization. Stitch's pricing, even though I just used the free version, was not really that good because there were many options. I think it's not that impressive because there were many options, other AIs like Dora, which give free 3D design files. I would rate this review a 7 out of 10.

I mostly use Stitch for rapid prototyping; when we reach the sketching stage and have a big idea of what we want to create, I immediately get into Stitch to have an overview of how the final design might look or how the product might look. I use it mostly for either rapid prototyping or to get inspiration to get started.

I can recall an application we were building for learning, which we designed targeting high schoolers. During the sprint we had for the first feature, we had to design before launch. The sprint could account for some part of the app, and we had to find a way to fill in those missing spots and missing interfaces, maybe for notifications, confirmations, and success pages. We didn't have time, so I went on to Stitch and using a prompt I got from ChatGPT, I was able to get something that was clean enough to use for the first launch of the project.

Stitch is a great game changer, especially for small design teams; it enables you to get from an idea of what you want to design or what you want to build to an actual design. It limits that friction where in the past we used to say, 'I don't have inspiration for this particular screen,' or, 'I don't know how to go about this specific layout.' Stitch gives you a rough overview of how you can go about it. It speeds up the design flow, especially for startups that are trying to grow as much as they can.

The recent feature that was launched with the design canvas, which enables us to modify items directly from the canvas, is one of the best features Stitch offers. They're slowly becoming more similar to Figma, but it's a really great way to explore more and more. It helps me isolate specific parts of the designs that I want to modify and get those little edits faster. It's quite similar to Figma, but not yet at the Figma level. I have a lot of hopes towards Stitch and believe they will release other versions with other iterations which will bring that product to the next level.

I saved a lot of time getting from having no design inspiration to having full-fledged designs. I was able to reflect on what I might want to see added on Stitch. The designs that Stitch produces sometimes cannot really be used for final launch, but I understand Stitch was designed just for rapid prototyping and for teams to get from the point where they just have an idea to having an actual product.

What I would want to see added on Stitch is different design styles. For instance, if I want to go with a minimalistic style, a brutalist style, a soft UI or neumorphic style, I would appreciate Stitch exploring these different ways of designing.

In terms of improvements, I have really tried to think about what improvements could be added to Stitch. So far what I have in mind is turning it into Figma, but that isn't the goal of what Google has in mind concerning this product. Given that Stitch was designed for rapid prototyping and to get ideas out there, Stitch right now is quite good.

I have been using Stitch for three years now.

Stitch helps immensely because in just a day, we are able to cover the work that would normally take two to three weeks worth of design work nonstop. Stitch enables us to get things done and have something to show. It's a real game changer.

Regarding the interface, I would say it is quite good and intuitive enough, and it is very easy to navigate. The interface is quite clear, and without really having to think a lot before getting things moving, everything is quite cool. You can go from not having any idea to getting a lot of interesting material that you can use as inspiration for your work. That is something that saves me a lot of time. Every time I get on Stitch, I feel energetic because I know I am going to get things done. My overall review rating for Stitch is three out of five.

I have been using Stitch for the last five years.

My main use case for Stitch is to ingest SFDC data and also Google Analytics, Facebook Ads, and GA4.

I use Stitch as a data ingestion tool for SFDC, and I load the data into Redshift. I use the Bulk and REST APIs to do the incremental loads. I also use it for Google Analytics and Facebook Ads.

I think the best feature Stitch offers is that it handles deleted records.

Stitch's ability to handle deleted records is a standout feature for me because if a record is deleted at the source, I can easily track it with soft delete and all that functionality.

Stitch has impacted my organization positively, as I have both positive and negative aspects with it. One positive aspect is that full loads are free, so whenever I see data issues, I can go for full loads. At the same time, I need to look at the limitations, such as API limits.

Stitch has helped my organization achieve better data management, making it easier. Better data management means that Stitch helps my team access data faster and reduces errors.

I wish Stitch could handle changes and updates to data better.

I think improvement is needed in the licensing process.

I have been using Stitch for the last five years.

I find Stitch stable in my experience.

My experience with customer support for Stitch has been very bad.

I did not previously use a different solution before Stitch.

I think I have seen a return on investment with Stitch in terms of time saved.

I estimate that my team saves maybe a few hours per week using Stitch.

My experience with pricing, setup cost, and licensing for Stitch shows that it is a bit costlier, and right now, with the merger of Stitch and Talend, the licensing process is a bit clumsy.

Before choosing Stitch, I evaluated other options such as Fivetran.

I do not want to add more about the features of Stitch.

I do not have any other improvements needed for Stitch that I have not mentioned yet.

My advice to others looking into using Stitch is to consider the support model.

I think the interview process is good and does not need any changes for the future.

My review rating for Stitch is 5.

Our main use case for Stitch is several integrations, such as Zuora, Salesforce, Airflow metadata, and a few more pipelines.

We use OAuth authentication to connect Stitch, then set up the pipeline using an API key or some other authentication method, and then put all the data inside Snowflake, as we use only Snowflake as a target.

We try to gather and ingest all data possible in the raw schema or raw database, then later we will process it. We try to do everything at once and load the data we need.

Easy setup and easy change management are the best features Stitch offers, along with a good admin panel.

Regarding the easy setup, I really only need to put in credentials, such as an API key, username and password, or whatever type of connection the provider uses. You can easily declare the schema, columns, and tables you want to integrate or extract, and then you can easily press the button and move on and track your progress. Logging and debugging are already nicely set up. The admin panel is easy to use, and you can see everything you need and it is easy to spot any kind of error.

The easiness of debugging and clear log messages are valuable features.

We can easily move and do time-to-market for a new pipeline and new integration, positively impacting our organization.

Stitch should definitely provide more extractors than it does now and provide the ability for teams to integrate their own extractors.

Stitch should definitely add more flexibility for users. For example, if I have something very specific regarding the source, I should be able to do it on my own and then publish it as a store so anyone can use it. Stitch should be more open.

I have been using Stitch for about six years.

I think it is adequate. Stitch can handle a massive amount of data, so I do not think that is a problem. It can easily scale. In this cloud era, it is not a big issue.

It was adequate. I had a couple of setup calls with them and they are doing fine.

We try to parallelly use a couple of others: Meltano, Fivetran, and Stitch.

We did not decide to switch; we use them parallelly because for some providers, we have no extractor.

We evaluated Airbyte among many others before choosing Stitch.

Change management is done on Stitch, by Stitch. Instead of spending a lot of time for custom integration, we are using Stitch and have an out-of-the-box, off-the-shelf integration tool that we can set up in a couple of hours.

I do not have clear answers on that because I do not have the exact metrics about the finance part of that. However, the main advantage is a very quick time-to-market.

It was adequate and good. I would say it could have a better pricing option, but that is what it is.

Stitch does not offer any specific advantage if you have an extractor, but it will do it fine and provides a nice and clear experience.

I would say Stitch is a good tool and a great tool. If you are not an expert in engineering or familiar with any kind of data engineering process, you can easily set up what you need and choose the destination of your choice and then you can move on and continue your work. This is a nice tool. I would rate this product a seven out of ten.

I have been using Stitch for the past two years in two different companies. My main use case for Stitch is connecting to third-party apps, extracting the data out of them, and transferring it into our data warehouse.

A specific example of a third-party app I connect with is Shopify, where we are selling products. In Shopify, we have all the sales database, and we connect to that database through Stitch to our BigQuery in order to perform analysis on our Shopify data.

We work with many apps connected to our data warehouse through Stitch. In addition to Shopify, we have all the Facebook data, metadata, and TikTok data.

The best feature Stitch offers is the pricing plan; we know up ahead how much we are going to pay, and the prices are quite affordable. Compared to other data integration tools I have used, I think the price is quite good since we are a small startup and are price-sensitive.

The setup process for Stitch was pretty easy, with a plug and play approach where the data is immediately available. The UI is okay, and I think it is one of the easiest tools to use when compared to the competition.

Stitch has impacted my organization positively by providing easy-to-use data, so no data engineer is needed. I am able to manage my data integration without needing a dedicated data engineer.

To improve Stitch, I think the explanation about the errors could be simplified because I currently use ChatGPT to understand what is wrong with the connection or with the run. Another thing that I am missing is that Stitch cannot connect to all databases or third-party apps, such as Amazon Seller, which I cannot use Stitch for. Outbrain is another platform where we publish commercials, and I cannot get the data out of it, which is frustrating because I need to use the competition, Fivetran.

I believe that Stitch does not have support because every time I needed support, I was only able to interact with a bot, and I never received a solid answer. Most of the time the bot shifted responsibility to the third party.

Neutral

My main use case for Stitch is getting design inspirations. I have used Stitch to get design inspirations and to automate my workflow by generating design inspirations to get a few tips for Figma conversion.

Stitch has had a positive impact on my organization through the turnaround time because we can quickly deliver our deliverables from our end to our organization.

For example, 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 never get into the real projects right now, so for POC-related tasks, we quickly release our deliverables using Stitch.

The best features Stitch offers are that I can copy the designs directly to Figma. Copying designs directly to Figma from Stitch has helped my team and me tremendously because in the beginning, we had to design the application from scratch, but now we can get inspirations from Stitch and copy directly from Stitch to shorten our time.

Stitch can be improved by being able to connect the design system to it, and being able to design any components from that design system would be the best improvement.

I also think that if we could edit the design in Stitch itself, that would be another valuable improvement.

I have been using Stitch since it was released a few months back.

Stitch is stable.

Previously, I used Lovable, but after using Lovable, it gave repeatedly the same solution. I switched from Lovable to Stitch.

The return on investment I see is time saved.

As of now, we did not buy directly; we just used the free account.

My advice to others looking into using Stitch is that it will give multiple solutions for your problem, so you can use it without any second opinion. I did not partner with Stitch, so I cannot comment on that. I would rate this product an 8 out of 10.

My main use case for Stitch involves MVP projects. An example of how I use Stitch in my MVP projects is a share purchase project that allows you to find the best prices for products in the region.

The best features Stitch offers include the ability to convert images to HTML. The image to HTML conversion helps me in my projects because it allows you to acquire professional designs without starting from scratch. Stitch has positively impacted my organization by allowing us to create MVPs quickly. This means for my workflow that it allows you to test new ideas quickly, which is beneficial.

I have noticed that the interface between the functions is somewhat confusing, but it works adequately. The conversion to Figma is not effective. To improve Stitch, I suggest developing a featured interface that is easier to use. Additionally, the functions of nano bananas within Stitch were unclear.

I have been using Stitch for three months.

I find Stitch to be stable.

Stitch is highly scalable and fast.

Previously, I used a different solution, which was the EA Model Sonet.

I have seen a return on investment because I received a return on the time invested in the project.

My experience with pricing, setup cost, and licensing is that it offers a fair price.

Before choosing Stitch, I evaluated other options, specifically Cursor IDE.

My advice for others looking into using Stitch is to use it to create good interfaces, but keep in mind that Figma does not work well. I would rate this review as a 7.