SnapLogic Reviews

Our main use case for SnapLogic is the integration of student data, some finance data, and some internal Stanford data processes.

A specific example of how I use SnapLogic for integrating student or finance data is when new staff, students, or faculty join Stanford; they have to be added to different workgroups or their email has to be set up, so many processes are done via SnapLogic integration. On the finance side, it involves processing data related to the Office of Development, where some gift processing happens. Multiple teams at Stanford, including the School of Business, use SnapLogic for tasks such as booking meeting rooms.

We use SnapLogic for various integration purposes, including integration from Salesforce to Oracle, from flat files to Oracle, and integration from FileMaker to Oracle, among others. Although many more integrations are running as pipelines, these are a few I can recall as an infrastructure team member.

The best features SnapLogic offers are its ease of development for pipelines, where the authentication and account configuration are straightforward, and it allows for easy connections to sources and targets, as well as simple transformations and making multiple copies of the same data. I find the development part very easy, especially from an infrastructure perspective, since we host all Snaplexes on-premises servers; upgrades are seamless, and the impact on pipelines during rolling upgrades is minimal.

The development interface is user-friendly, making the process of connecting to sources straightforward, especially when setting up accounts using any Snap or API, which allows anyone to use it easily. Making configuration changes or moving servers between environments is also very easy.

SnapLogic has positively impacted our organization by providing an alternative to Informatica, which was challenging due to licensing and other issues. With SnapLogic, we can now connect to various SaaS and cloud products, and its usage has spread across different departments, making it a central tool for both on-cloud and on-premises ETL processes.

Areas for improvement for SnapLogic include enhancing the documentation, especially by providing more complex examples in each Snappack, to cover various use cases that different team members may encounter.

Another improvement I suggest is enhancing the monitor page on the dashboard to allow quicker and more efficient access to historical data, as it currently becomes slow and sometimes hangs when accessing older data.

I have been using SnapLogic for six to seven years.

I have been using SnapLogic for a while, and I believe the tool has become more stable, although there are still monitoring features I have had to build on my own. More robust APIs would assist anyone looking to automate processes.

My advice for others looking into using SnapLogic is to participate in training sessions provided by SnapLogic support, which can significantly help new users understand the UI and its functions through self-learning videos. I would rate my overall experience with SnapLogic a 9 out of 10.

SnapLogic is used in three different areas within our organization: primarily data ingestion, reverse ETL, and the most critical aspect is building APIs. We build APIs in SnapLogic that get exposed to both third parties and internally.

A specific example of how I use SnapLogic for building APIs is in our CPQ integration, where a sales representative can make a quote by using Salesforce to call the API we created, connecting to our internal systems for customer and product information as well as Zuora to create a preview order, including calculations such as taxes. Once the quote is complete, the salesperson makes another call when the order gets created, pushing that order into our provisioning system and Zuora for billing, all managed with another API. Additionally, once the order is fulfilled in Zuora, we receive an event through a real-time API that pushes data back to Salesforce.

In addition to the CPQ example, we also create or transform data in Databricks using SnapLogic to send data back to our various systems. One of the more complex use cases involves sending emails to Iterable, as the data in one system is stored in a very structured way, while Iterable uses a more complex JSON structure, consuming the most memory and resources in our SnapLogic nodes.

The best features SnapLogic offers include ease of use. I have a lot of experience with other tools such as Informatica, Talend, Boomi, and Pentaho. At Asana, when I needed to start onboarding new team members and building the team, SnapLogic was already in place, allowing me to build the first integration in about half an hour and understand how the system works, which is critical for time to market. This capability reduces the need for additional resources or capacity during significant deployments or projects.

SnapLogic's user interface and workflow design aid my team in moving quickly. The concept behind the name Snap is that you can easily connect different features. For instance, remapping a database query into JSON for a different application is straightforward and feels like building a puzzle. With features such as SnapGPT and systems that generate JSON for SnapLogic, the process becomes very easy. When I started five and a half years ago, we scaled up from having five developers due to increasing needs, and with advancements in SnapGPT, we managed to reduce our contractor base while delivering more in less time.

SnapLogic is very feature-rich, and I appreciate the predefined snaps. For example, integrating with NetSuite has always been challenging for us, but after a recent upgrade, we updated our connector and it did all the work for us, finishing what would have taken weeks in just a couple of days, including testing.

SnapLogic has positively impacted our organization by improving time to market and reducing our reliance on experienced Python developers or hardcore coders to generate outputs and deliver results. Consequently, the platform has significantly helped us with timing and costs. It also offers flexibility with our use of Groundplex and Cloudplex; we utilize Cloudplex for internet-friendly tasks and Groundplex for secure tasks that cannot have data leave our premises.

From our development perspective, we have requested SnapLogic to enhance their SnapGPT to be friendlier, improve documentation capabilities, and enable more Cursor-based type development. While not all developers are fond of the current environment, SnapLogic has been responsive to our requests for improvement, often providing fast solutions for testing and implementation.

Additionally, we wished for a better implementation of the GitHub integration, as the existing method resembles older practices, where pushing a pull request involves pushing an entire package. Fortunately, they have implemented new features that allow us to be more flexible in this regard, but we still desire the ability to manage multiple folders more efficiently rather than having to create a separate repository for each folder.

My advice for others looking into using SnapLogic is to conduct comparisons of the competition without falling for their marketing tactics. After extensive analysis, including RFP processes and scrutinizing details, I believe SnapLogic stands ahead of other tools, especially when it comes to handling large data movements under the radar. It is important to seek tools that facilitate both data delivery to a warehouse and capabilities for transformation and reverse ETL.

SnapLogic has been an exceptional partner in implementing solutions and maintaining constant communication, particularly during a recent downtime issue, where their updates and care for customer relations were greatly appreciated. I would rate this review an eight out of ten.

My main use case for SnapLogic is developing pipelines to transfer data from a source into our Dynamic CRM. We are thinking about using APIs and more with AI within our pipelines, and hopefully, in the future, we want to develop pipelines to write into our data warehouse once we have that implemented.

SnapLogic offers excellent features based on my experience. The snaps are very easy to work with, and it is straightforward to understand what the different kinds of snaps are available and when to use them. I specifically like SnapGPT, which has been very useful. As a solo developer at Mind, having SnapGPT to perform code checks or identify any risks within my pipeline has been invaluable.

SnapLogic has positively impacted my organization because our previous ETL tool called Scribe was going to be decommissioned, and we really needed a different way of transferring data from a source, mainly a CSV file, into CRM. Without it, we would not be able to import any of our CRM data into our Dynamics, which would prevent our CRM users from performing supporter relations, handling our supporters, and thanking them.

Regarding my experience with SnapGPT, I always ask it if my pipeline has any risk. When there are risks, such as not catching a certain data type, it lets me know that perhaps instead of returning an empty string, it should return null. It has been useful for helping me develop code. Recently, I wanted to take a string where it identifies the first part as address line one, and I wanted to search for the postcode within the long string. SnapGPT was able to give me an expression that allowed me to take part one as address line one, and because the UK postcode has a certain way of being written, it was able to identify where the postcode is within the string.

SnapLogic could improve its notification system. When a pipeline fails, the notification sometimes comes back as not very useful. I had a recent case where it just told me that a snap had failed unexpectedly without providing any reason, which is not helpful for troubleshooting, especially on the live system. To resolve this, I had to manually validate the pipeline to find the issue, which allowed me to see the data running into those individual snaps and what the error was. I would like to see if the execution can show the data flowing into those individual snaps and provide the same kind of error that I receive when validating, as that would be much more useful.

I would give SnapLogic a higher rating if the error handling and notification were more specific and user-friendly to read. Apart from that, I do not think there is anything else that I can identify.

I have been using SnapLogic for a year and three months.

In my experience, SnapLogic is very stable.

The scalability of SnapLogic is good. We develop our pipelines to be quite robust so they can be scalable in the future if users want more complex pipelines. Mind is quite early in using data, so the data we currently work with does not have that much complexity.

The customer support for SnapLogic is excellent.

SnapLogic has positively impacted my organization because our previous ETL tool called Scribe was going to be decommissioned, and we really needed a different way of transferring data from a source, mainly a CSV file, into CRM. Without it, we would not be able to import any of our CRM data into our Dynamics, which would prevent our CRM users from performing supporter relations, handling our supporters, and thanking them.

While I do not have any metrics, SnapLogic has definitely saved a lot of time because of how easy it is to implement designs for our data transfer. It has definitely saved time and streamlined many ways of working. Previously, a person would drop a file and then have to perform a lot of data manipulation within the file to push it into our Scribe process and then into CRM. SnapLogic saves a lot of users' time and reduces potential errors that could occur from a person manually updating the data.

If others are looking into using SnapLogic for Dynamics 365, my advice is that there is a significant learning curve in understanding how SnapLogic and Dynamics should communicate with each other. There is not really much documentation regarding using SnapLogic and Dynamics together, so there are quite a lot of nuances to figure out before being able to connect the mappings to the correct fields in Dynamics, using the OData bind functionality, and sometimes needing to know whether to use null or empty strings for certain fields. This knowledge would have been valuable to have at the beginning. I would rate this review an 8 out of 10.

My main use case for SnapLogic is dragging and dropping files from one SFTP to another SFTP.

A specific example of a workflow I set up using SnapLogic is picking up files from our SFTP which our system creates and drops there, then moving them across to our reconciliation team, a third party that does our reconciliation on an automated schedule.

The best features SnapLogic offers in my experience are that once you have your head around it initially, it is quite easy to use and can take away time from the development team because people with less technical skills can use it.

The learning curve at the start took maybe a couple of weeks just to know where things were, but there was a tutorial which helped with that, so for example, displaying the documents made it easier for less technical users.

SnapLogic has impacted my organization positively because many of the automations we made with dragging and dropping files used to be done by a human, so now there is less human error and it saves the team as it requires fewer people to do the work. There are two people less from a seven-person team now thanks to SnapLogic. I would estimate maybe an hour a day is saved, although I do not have exact numbers on time saved.

The only thing I do not prefer at the minute about SnapLogic is when I go into the monitor, it can be a bit slow, so when I am trying to diagnose why something went wrong and I am searching, it can take a bit of time.

SnapLogic could be improved in the monitor performance area.

I have been using SnapLogic for about two and a half years, the whole time I have been at Vitesse.

SnapLogic has been stable in my experience with no crashes.

Regarding SnapLogic's scalability, we have not needed to scale it as it has been stable.

The customer support for SnapLogic has been good as whenever we have raised an issue, I get a response within 24 hours.

I did not previously use a different solution before SnapLogic, as SnapLogic was already in use at this company before I got here.

The learning curve at the start took maybe a couple of weeks just to know where things were, but there was a tutorial which helped with that, so for example, displaying the documents made it easier for less technical users.

I have seen a return on investment with SnapLogic.

Regarding SnapLogic's AI capabilities, it works as expected.

I would describe my experience with SnapLogic's integration capabilities as very easy; the ones I have used have been very easy.

I would rate SnapLogic's documentation and learning resources as thorough and easy to get to when you click through the snaps to access them, so they were helpful when I was getting started.

Overall, the performance and speed of SnapLogic, aside from the monitor I mentioned, have been good because I have never had any issues.

The reliability and availability of SnapLogic have been good, as there was something on our side where the node restarted, but there were no major issues I have seen.

I would describe the ease of maintenance for SnapLogic as simple to keep things running smoothly.

My advice to others looking into using SnapLogic is to take your time and go through the tutorial when starting, just to get your head around everything before making a decision. I would rate SnapLogic a 7 overall.

I use SnapLogic for e-commerce, marketing, data analytics purposes, airline, banking, and integrating for ETL and ELT concepts.

A specific example of how I use SnapLogic for these purposes is an ERP system such as SAP, Salesforce, or JD Edwards, where we collect the data and perform the transformation as per the requirement, then parse or format them as required by the target source, and then send the data to the target systems.

Recently, for an integration for financial analytics, we needed to collect raw data from more than seven to eight ERP systems and then load them into a data lake target system. In that case, we needed to build the transformation and mapping parts for each ERP, then load into the data lake using the same structure or pipeline without rework, which was quite helpful in that integration.

The best features SnapLogic offers are APIM and SnapGPT, along with NLM, MCP integration requirements, and the usual real-time integration and ETL, ELT aspects.

APIM has helped me with policies because we have multiple sources and targets, and we follow structured architectural functionalities within our organization, allowing certain systems to use specific authentication methods, while others require different authentications, making APIM quite helpful for integrating between systems. For SnapGPT, it assists in optimizing pipelines and addressing any AI-related questions, which is particularly useful for my team who manages development and design.

SnapLogic has positively impacted my organization by aiding in the collection and transformation of various data and supporting future analytics and financial topics. The design aspect of SnapLogic is quite easier and more understandable, and it is noteworthy that you do not need to be a dedicated SnapLogic developer, as other integration developers can quickly gain a good understanding after working with it for some time.

The ways SnapLogic can be improved depend on specific requirements and business needs, so I leave it to each individual business to determine its usage accordingly and weigh the pros and cons.

I do not have any specific outcomes or metrics such as time saved, cost reduction, or improvements in analytics to share at this moment.

On a scale of 1 to 10, I would rate SnapLogic a seven. I give it a seven because it does quite well for our organization. While we had another integration system earlier, SnapLogic's ability to handle the latest futuristic integrations and its compatibility with various target systems is impressive, though I believe we need to explore other requirements or possibilities to see if we can achieve more with SnapLogic, which might raise my rating to an eight or nine.

Regarding SnapLogic's AI capabilities, the governance and security are good aspects since it is controlled by SnapLogic itself for CloudPlex. The accuracy and reliability of output from SnapLogic works similarly to other AI agents, but more use cases need to be conducted to fully understand it.

I advise others considering SnapLogic to look into some use cases and case studies to determine if it suits their business requirements. My overall rating for SnapLogic is seven out of ten.

My main use case for SnapLogic is to use the monitor tab to monitor the daily pipelines, the sales reports, and to check on the failures which are happening. When some failures occur, I utilize SnapLogic Designer to make the changes so that the pipeline runs successfully.

A specific example of a pipeline I've worked on recently is the daily sales report which we deliver to the business during the early business hours. It is a critical report, and for that file, we faced the issue of duplicates. Together with the help of my senior teammates and colleagues, we created a pipeline that removes all the duplicate entries. It was fascinating because SnapLogic has inbuilt Snaplets that we can directly drag and drop and develop a pipeline with very minimal code. Moreover, we can provide different kinds of parameters that can be versatile and changed according to our requirements. This is one of the pipelines I've worked on recently, about one or two weeks ago, and I monitor it daily after deploying it into the prod environment.

Most of the pipelines I work on are related to building up to loading the data into sales. In my current project, the data from SQL Server and Redshift is loaded into BigQuery and Oracle tables. In SnapLogic, we developed some transformations, such as removing duplicates and adding other parameters to remove inconsistencies. These are the types of pipelines we use in SnapLogic to transition data, functioning as ETL, by extracting from SQL Server or Redshift, transforming in SnapLogic, and loading it back into GCP and Oracle.

One of the best features SnapLogic offers is its user-friendly interface. I was not trained in using SnapLogic; I was trained in Informatica, which is also a data engineering tool. However, when I first started using SnapLogic, any person with minimal knowledge in data engineering can easily understand how SnapLogic works because it is clearly segregated into Monitor tab, Designer tab, and a Manager tab. The role assigned in your project defines which tab you will use the most. The user interface is important, and the inbuilt Snaplets that we can directly drag and drop to create different kinds of pipelines also stand out.

The drag and drop functionality and the tabs make my daily work easier compared to my experience with Informatica. In Informatica during my internship, creating mappings took a lot of time and effort since we needed to leverage Mapplets. While we can create one mapping and use it multiple times, there is no help from the application side. There are some transformations most users need that are not inbuilt in Informatica. In contrast, SnapLogic provides inbuilt Snaplets, such as creating and closing an audit ID, removing duplicates, joining tables, writing to Oracle, files, XML, SF, SMTP connections, and more. These Snaplets can be directly used rather than developed in every pipeline.

Since moving to SnapLogic, we have observed fewer errors compared to other tools, such as connection failures or network errors. We have also developed pipelines in SnapLogic capable of notifying us about long-running processes. For instance, if a pipeline that typically takes one hour runs for more than two hours, it automatically triggers an email alerting us to focus on that specific pipeline. This feature significantly reduces the need for continuous human monitoring, demonstrating how SnapLogic truly assists us.

I have only been using SnapLogic for about a year, around eight months, so I am unsure of the required changes. However, I believe that since most tools are now integrating with AI to assist new users, incorporating an AI tool could be beneficial.

Sometimes there are glitches when moving a design pipeline from the development to production environment.

I have only been using SnapLogic for about seven months.

SnapLogic is very stable.

SnapLogic is very scalable, and it can be adjusted based on our requirements, considering the organization type and the data it produces.

I have not used customer support directly, but I have utilized the integrated helping websites, which have been very helpful when I first started using SnapLogic.

Negative

I learned from my colleagues that two years ago, all our transformations were carried out in Informatica. Because of the inadequate infrastructure in Informatica, our team suggested transitioning to SnapLogic, which the client accepted. After comparing workflows in Informatica and pipelines in SnapLogic, we found that the number of errors due to network or connection issues is much rarer in SnapLogic compared to other tools. The decision to transition to SnapLogic was very beneficial, as it helped the client build a secure and robust environment for their data.

We transitioned to SnapLogic due to the lack of proper infrastructure in the previous tool.

My seniors evaluated different options, including SnapLogic, improving the infrastructure in Informatica PowerCenter, and using PySpark, but they ultimately chose SnapLogic over the other options.

My advice for others looking into using SnapLogic is that it is really easy to use. Anyone with minimal knowledge in data engineering or ETL can easily transition into a SnapLogic developer or start using SnapLogic. I have mostly covered all the topics concerning SnapLogic that I appreciate, and I have provided some suggestions that I hope would facilitate ease of use when integrated. I gave SnapLogic a rating of eight out of ten.

My main use case for SnapLogic is to load data into our CRM, which involves normal ETL and extensive data cleaning before putting it into the CRM.

A specific example of a project where I used SnapLogic for ETL and data cleaning is when we receive data from the bank and use that spreadsheet to find a contact in the CRM and then create income records on the spreadsheet and push it into the CRM. I use SnapLogic to execute the process, and it is all working well now, following business logic, and the process is very quick and easy.

These days we are trying to use SnapLogic to integrate it into an API to call those data and push it into the CRM instead of picking up files, and I think that is the next stage we are going into, but as it develops, we will see what more things we can use SnapLogic for.

The best features SnapLogic offers are the drag-and-drop features and the low-code capability, which is very good.

The low-code aspect of SnapLogic stands out for me because the interface is good, but the speed is exceptional. You do not need to know much to use it; I can easily train somebody without a background in coding to use a few Snaplex and connect them together with some minimal configuration and just get the job working. The ease of use is exceptional.

SnapLogic has positively impacted my organization because we have been able to cut down manual import into the CRM by over 50%, which means that the data quality is improving over time. This improvement means a lot of business processes that run on the speed at which data is available in the CRM are able to run better, improving the performance of our fundraising team in terms of reaching out to supporters and supporting supporters in any fundraising activity they want to do for us.

I think SnapLogic could be improved if the Snaplex has a way to change for people that want to write code, or to convert code to the Snaplex. There should be a way of switching the Snaplex into a base code so that you can add to the code and then save it, which would then be converted into logic on the front end. Having an alternative code injection into each Snaplex would be beneficial. For instance, in the Dynamics search Snaplex, sometimes you might want to search and filter by other entities. Right now you need to connect other entities together to accomplish that, but this should be possible if you have a way of injecting code and making SnapLogic run through the code and calling both entities together and doing the filter and pumping out results to be used, rather than each Snaplex doing only one thing.

I have been using SnapLogic for a little over a year now.

SnapLogic is stable in my experience.

SnapLogic's scalability has been very good, as we have not had any issues around scalability, whether it is a very small import or a very large import. We have not seen any depreciation of service speed due to load or quantity.

The customer support for SnapLogic has been great; they have always been there to take us through whatever we need.

Before SnapLogic, we previously used Tibco Scribe internally, and one of the main reasons why we switched is that Scribe was at the end of life and being discontinued. Additionally, Scribe is a bit rigid in terms of the way it works, and we needed something that does not require someone with technical knowledge to use.

We have seen lots of time saving in our approach using SnapLogic, and the number of people needed to do import is now reducing because we are able to automate everything, and things can be manipulated and tweaked as needed. This automation frees up a lot of time for other people to do something else, meaning we do not need to recruit more staff; we can use the hands internally to accomplish whatever we need to accomplish.

Before choosing SnapLogic, we evaluated other options, including Blackboard and a few others I have forgotten now.

My advice to others looking into using SnapLogic is that it is a very good product to use, but you have to consider your scenario and business case, and ensure that you research Groundplex and the Cloudplex so that you know which one is actually better for your organization and which one actually suits your organization in terms of implication, application, and the governance approach in terms of the UK approach versus the US-based product which SnapLogic is.

I have additional thoughts about SnapLogic, and I think it is been a great product, something I will recommend.

Regarding SnapLogic's AI capabilities, I think it has been good, but over time it will improve further; the accuracy of the result is good, but it can always be better.

I give this product a rating of 9 out of 10.

My main use case for SnapLogic involves migrating data from legacy to the latest product. We are migrating heritage products to the latest products using SnapLogic.

One specific example of how I used SnapLogic in these migrations is that we take data from the source using SQL views, perform some transformations in SnapLogic, and once transformations are completed, we move data into an interim database, and from there we push that data to the target system using APIs.

The best features SnapLogic offers include being lightweight and easy to integrate, allowing us to easily move data from source to target. Compared to other tools I have used, such as SSIS which is quite complex, SnapLogic has straightforward snaps that allow us to easily join to other snaps and push the data.

Additionally, SnapGPT is one of the best features currently, as it helps us review existing pipelines and obtain documentation and test cases from SnapGPT.

SnapLogic has positively impacted our organization, as we are using this tool to migrate existing legacy products to the latest products, which has also increased our revenue.

Using SnapLogic saves a lot of time when we develop pipelines. Once we hand over those pipelines to the professional services team, they run them to migrate the legacy products to the latest products, which takes one or two days. Importing data from Excel systems, especially when dealing with thousands of records, takes minimal time thanks to SnapLogic. Customer satisfaction improves as professional services teams successfully migrate legacy products to the latest ones.

SnapLogic currently offers SnapGPT with more capabilities compared to earlier versions, but there is still room for improvement compared to other AI tools, particularly in areas such as viewing historical data and automatic file reading which would be very useful.

The interface still has options for improvement. While it has been enhanced in recent versions, it is often difficult to identify snaps when developing large pipelines, requiring a lot of zooming. A simpler option to see the snaps would be beneficial.

After execution, it is challenging to know how much data has been processed, and there is a need for better AI integration since it lags behind other tools.

I have been using SnapLogic for around two years.

SnapLogic is stable in my experience.

SnapLogic's scalability depends on how we configure the Snaplex. If there are options to scale up or down on demand, that would definitely be a great feature for SnapLogic.

I can give 70 out of 100 for customer support.

I previously used SSIS before switching to SnapLogic.

I did not switch from SSIS to SnapLogic intentionally. Rather, after building the data marts with SSIS, we had the opportunity to work on SnapLogic.

I have seen a return on investment with SnapLogic, particularly because we are successfully migrating legacy products to the latest products, which increases our revenue.

I was not involved in the pricing, setup cost, and licensing, so I cannot provide details about that.

I advise others looking into using SnapLogic to definitely give it a try, as it is lightweight, easy to learn and integrate, making it simple to migrate data between systems without needing to save anything into SnapLogic itself.

Improving customer support and AI capabilities will help SnapLogic excel in the future. I would rate this product 8 out of 10.

The main use case for SnapLogic is data integration between different applications and automating data workflows. We use it when we have a different set of products where we have to migrate data from one product to another product, such as from our legacy product to the new product.

For example, we had one data migration project where our Priya customers had to be migrated to the new product, which is the Devonway application. We used SnapLogic to migrate the data from Priya to Devonway.

The most important features are the pre-built connectors that allow us to connect to different applications and various data-related Snaps where we can migrate data from one place to another. SnapLogic has the best administration capabilities where we can manage all the built-in automated data flows very easily. The migration from dev to test and test to prod is straightforward, and the deployment is really easy. There is no need to maintain an additional administrator for that particular function. The Monitor tab provided in SnapLogic is of great help, where we can monitor and see the logs wherever there are errors in our data migration pipelines. Additionally, SnapGPT, the AI feature given in SnapLogic, is also a great feature where we can provide a prompt to get simple pipelines built using SnapGPT.

SnapLogic has impacted our operations to a great extent. Currently, we started with other tools as well, such as SSIS, which is not a cloud-based solution. We had to move to SnapLogic where the managing and maintenance parts are definitely really easy to maintain those integrations. All the migrations that we have built are primarily on SnapLogic. Those migrations are very successful, and we are able to move data from one platform to another platform very easily. The customers are happy with the data migrations that we are doing with SnapLogic.

There should be documentation for advanced integrations that would definitely help beginners. When complex data migrations are involved, if the documentation is provided in SnapLogic, it would definitely ease new joiners and beginners to look into that and build those complex integrations.

One thing is that we are using Claude AI. To connect to Claude AI, there is an MCP in place in SnapLogic, but the documentation, examples, or use cases would definitely be helpful for us to use Claude more efficiently in relation with SnapLogic.

We have been using SnapLogic for the past three years.

Not much else, but it has helped a great deal. Even beginners who joined our team are able to use SnapLogic without any SnapLogic knowledge as they have prior knowledge on data engineering with other tools such as SSIS and Azure Data Factory. That knowledge is more helpful to get familiar with SnapLogic Snaps and get started from there. There is some learning involved in understanding complex integrations. The basic ones are straightforward, whereas complex integrations need more learning. If SnapLogic had documentation on advanced integrations, that would be more helpful for beginners.

SnapGPT is a feature that would definitely save a lot of time and work. If I need to build a simple pipeline, I don't need to spend the time to do it manually. I just need to give a prompt for building the pipeline and provide some use case to SnapGPT so that it can build it for me. I would definitely say that once the pipeline is built, I only need to spend ten percent of the time modifying the required things in the pipeline. That would really help.

Time is definitely saved. The best example is that in other tools, we don't have these many pre-built connectors where we can directly connect and do data transfer from one place to another. We had to use some third-party tools to connect to the source and destinations to do those data movements. That definitely saved a lot of time. We also had some Python scripts that we had to write for some of the integrations. Those things have now been migrated to SnapLogic, which definitely saves a lot of time and cost as well.

Every tool has some advantages and there are some other things that need improvement. SnapGPT is solving only basic problems. If a complicated pipeline is given to it, it needs more training. More questions will be asked, and sometimes it is helpful in resolving our issues and sometimes it is not. Every tool needs some improvement. For that reason, I would give eight out of ten.

I would say that SnapGPT is currently around sixty percent accurate. Reliability as well, I would rate at sixty percent.

SnapLogic is an excellent iPaaS tool which would definitely reduce the time and cost.

SnapLogic is my primary automation and integration platform that I use daily. A specific example of how I use SnapLogic day-to-day involves a number of different syncs, such as having CRM data from Salesforce syncing over to our Zendesk instance for our support teams and similarly, Salesforce going to Marketo for our marketing teams. We have various third-party platforms that we're sending logs to, such as Elastic and Zilla for security and governance, and we have various data transformations, gathering and aggregating data from various systems and then spitting that out to dashboards and Google Sheets or Tableau in various different places.

We have been focusing on AI use cases with SnapLogic lately, specifically on different sales-focused ones like a daily task looking at different Salesforce reports and trying to gather various context from Salesforce and maybe some other different systems to create a full context picture using an LLM to aggregate that, put together a report and send that on to some of our reps for them to action on.

The best features SnapLogic offers are its ease of use, flexibility, and within the interface itself, being able to rearrange the different snaps and easily see the flow of data going through the pipeline. Having the multiple outputs, being able to validate and preview data is extremely helpful in development. It is fairly straightforward and easy to use and can quickly get something up and running, at least for development.

The ease of use in SnapLogic comes from a lot of the pre-built account features, making it easy to use the different snaps for various platforms and getting the authentication portion straightforward. If I am doing a more traditional development thing, getting that authentication piece can be a bit time-consuming, and then being able to share those across multiple pipelines is extremely useful. The layout, as I mentioned, makes it easy to see how data is flowing through the pipelines, which makes it really easy for me to build and if I need to troubleshoot a pipeline someone else built, it is fairly easy to get in there and understand what is going on, even if I have not seen it before.

SnapLogic has positively impacted my organization as it is my primary automation platform and integrations, touching pretty much all of my major systems. It integrates and syncs data between all of my major platforms and has created more of these time-saving automations and the AI-assisted ones, which are bringing quicker calls to action for my teams in critical places. It has been a net positive for my team and the organization.

One thing I do not like about SnapLogic is some of the pre-built snap packs. If I want to integrate with a new system, I have to pay to get access to those. There have been a couple of instances of just different account types that I was not able to get working within SnapLogic and had to use a third party to get that data. Generally having to pay more to get access to the full feature set is a downside.

Regarding SnapLogic's AI capabilities, I find that the AI capabilities for the most part are locked behind pay, and I have not purchased many of them. I do use SnapGPT occasionally and know some other teammates who have recently gotten access and have not used the platform before tried that, but as we reviewed the pipelines that it built, they were not exactly great and we had to go through and fix a lot of things for them. It is nice when I am developing and trying to figure out an expression, as it is generally quite useful, but I cannot really speak much to the security and governance portion of it.

Regarding SnapLogic's AI capabilities, I think its accuracy and reliability of output are quite good with the expressions, but in my limited experience, the pipeline builder portions of it have not been great.

I have been using SnapLogic for roughly two and a half years.

SnapLogic is stable for the most part, although there was a pretty significant outage maybe two to three months ago, but other than that, it generally is.

The scalability of SnapLogic has been great.

I have not really used customer support much.

I was not on the team at the time we switched from Workato, but I know we were drawn to SnapLogic because the feature set and integration capabilities seemed a better fit for the team, and to grow long term.

I have seen a return on investment with SnapLogic. It is integrating all of my major platforms and we have a whole bunch of various automations for all different teams across the organization, and we are seeing a lot of time savings.

My advice to others looking into using SnapLogic is to consider the positive features I have mentioned before, as well as being aware of the downside of having to pay more to unlock more features. I give this review a rating of eight out of ten.