SnapLogic

I have been using SnapLogic for one and a half years on various multiple projects from the perspective of data migration and ingestions.

My main use case for SnapLogic is migrating some legacy product data to our newest products.

A specific example of a migration project I handled with SnapLogic involved our legacy product, which has multiple modules within it.

Regarding my main use case and other ways I use SnapLogic, we import the data as part of the ingestion process. We edit the data into an Excel tool in an Excel sheet and, using SnapLogic, read the data from the Excel sheet and load it into our newest product.

The best features SnapLogic offers in my experience include excellent REST APIs and batch processing, which is a standout feature.

Batch processing has helped us load around five to six lakh records within two to three hours, which involves loading thousands of records in a single shot. This helped our process reduce from eight hours to a couple of hours.

SnapLogic has positively impacted my organization because the professional services team has been running the pipelines and migrations very easily without any technical knowledge or dependency on technicalities.

This has made my team more efficient and freed up time for other projects. It significantly reduced the migration timeline for multiple customers, as there is no dependency on developers to run the migrations, allowing us to move to other particular migrations from the development perspective instead of running the same pipeline and staying on the same product.

API integrations are also really good to handle from a front-end perspective or any interface perspective regarding the features.

Regarding how SnapLogic can be improved, I think the Snaplex page can be improved without any downtime. There are some updates with SnapLogic that are not very stable before the release. This can be improved so that there will be no downtime impact for us.

I have been using SnapLogic for one and a half years on various multiple projects from the perspective of data migration and ingestions.

Regarding SnapLogic's AI capabilities, the accuracy and reliability of output are 50-50, but there is a lot of scope for improvement because I cannot rely on SnapLogic or SnapLogic AI or SnapGPT for the development which I am currently handling.

Regarding SnapLogic's AI capabilities, I think the governance and security are fine, but there is some scope for improvement with respect to security and access to personal level data.

The advice I would give to others looking into using SnapLogic is that it is a low-code tool and can be helpful for people who are just getting into software engineering or data engineering. This should help developers gain much confidence before starting with coding.

I am not really sure about the details of a business relationship with SnapLogic other than being a customer, but I am sure that we are a customer of SnapLogic. I do not know what kind of business relationship exists.

I would rate this product an 8 out of 10.

My main use case for SnapLogic is importing data to my CRM. I use SnapLogic by taking data from the JustGiving platform through an import file dropped into a specific location and loading it into my CRM.

The best features SnapLogic offers include its low-code nature, which makes it relatively easy for developers to pick up, and it has a wide range of connectors.

Reusability has been important for us with SnapLogic as well as being able to build MinePlexes and reuse them. We are also getting to grips with some of the AI capability.

SnapLogic has positively impacted our organization by allowing us to remove a big risk and cost in removing a legacy integration platform, and we have built the foundations to gain significant efficiencies in our integrations.

We want to get to grips with some of the automated testing functionality in SnapLogic, but we have not had the time to do that yet.

The main frustrations for us with SnapLogic have not been the technology, but the usual things of stakeholder capacity constraints and other hold-ups to the project.

One improvement that would be beneficial is better visibility of SnapLogic's environmental credentials.

I have been using SnapLogic for 18 months.

SnapLogic has been reliable for me with no downtime or disruptions.

SnapLogic's scalability as our needs grow or change is good.

The customer support for SnapLogic is very good.

I do not have any specific outcomes or metrics to share regarding time or money saved or how my team's workload has changed.

Learning SnapLogic for my team was fairly easy.

My experience with SnapLogic's documentation and learning resources is pretty good, although it always feels as though there is more to learn.

SnapLogic's integration with my existing systems and tools is easy and good.

SnapLogic's performance and speed when handling large data volumes are good. We have hit some snags, but we believe that is more on our CRM side than SnapLogic.

My advice to others looking into using SnapLogic is to go for it. I would rate this review as a 9.

My main use case for SnapLogic is integration with other systems, and I also use SnapLogic to replace a lot of our older systems that require integration.

A specific integration I set up with SnapLogic that made a significant difference for my team is called SGM, which is a Stanford Group Manager. It was originally written in Java and worked on a very old server, so instead of migrating the code and the technology to a new server, I redeveloped it using SnapLogic. Once I redeveloped it using SnapLogic, the integration part lagged a bit, so I still had to use some Java, especially for the integration with Active Directory. Even though SnapLogic provided resources and snaps for that, it was still inefficient.

Additionally, I had to integrate new harvesters, which are the logic side where they post events and process them. As SnapLogic matured, I rewrote part of that to spawn duplicate processes to execute and run a lot of the back-end integration, really cutting down on time, and as SnapLogic continues improving and I learn more about it, I continue to upgrade our current systems to make them more efficient and outperform a lot of our old systems.

One other benefit about my main use case with SnapLogic is the harvesters, which went through about four or five revisions before I created a standard template snap where I could use a property file to achieve the same information instead of repeating the pipelines or projects. Therefore, when someone does a request and they need this simple integration, I retrieve some information from a get and then post the information to a downstream system that could have multiple authentications, which I can now do all within a property file. This enables me to spin up a new harvester in SnapLogic within half a day, saving a lot of time.

I think the best feature SnapLogic offers overall is seamless integration. I basically only have to ensure I have all the right credentials to hook up a database, and therefore I don't have to write any of the JDBC that I had to do in Java for a connection. Other features I discovered include the versatility of authentication, though not all types of authentication are still available, and I look forward to seeing this improve so I can migrate other old applications over to SnapLogic.

SnapLogic positively impacts my organization by allowing me to do more application development integration in less time. However, when something brand new starts, there is still a big learning curve on how to implement it and streamline and use the features as best as possible. SnapLogic keeps improving, and as it improves, I have to go back and redesign slightly on our pipelines to make use of all these new snaps, leading to retrofitting that takes time.

I think SnapLogic can be improved by implementing more seamless logging of information. Currently, this is done through an error, but it would be best to have logging available on each snap that you can turn on and off, allowing you to configure a logging mechanism for where it logs. By having each snap available for logging, you can log all the information instead of creating a separate pipeline for logging.

Additionally, I suggest caching for snaps that are recursively called, particularly when logging in, authenticating, doing actions, logging out, and then repeating the process, which would significantly speed up operations, especially when querying an Active Directory because retrieving many members in Java takes about five seconds, whereas in SnapLogic, it takes a minute and a half for the same operation.

Regarding the new dedupe snap, I think the default setting should be changed from the current 80% match to an exact match, allowing for changes afterward, as I ran into issues during regression testing where a minor difference led to duplicates being flagged unintentionally.

I have been using SnapLogic for about seven years now.

SnapLogic is about 90% stable in my experience. There are times when snaps fail for unknown reasons, and sometimes after an upgrade, SnapLogic itself becomes unstable, but overall, it holds a 90% stability rate.

I believe SnapLogic's scalability is defined by our available budget. The more budget we have, the more resources we can obtain, hence allowing our pipelines and work to expand, making it challenging to assess without considering other external conditions.

I find customer support for SnapLogic to be top-notch, particularly with Dwayne. Most support from Zendesk has been very helpful, although some others are less so, as we often push SnapLogic beyond its limits, which leads to suggestions for improvements and inquiries about their design.

Overall, I would rate customer support ten out of ten. Due to Dwayne's involvement, I would even consider going past ten, given his strong interest in our work.

The solution I used before SnapLogic was Java, which was the only option available at the time for doing all the work.

I was not involved in the SnapLogic evaluation. When I joined, it was just in its infancy, and I went through the training while management made the decision to use it.

My advice for others looking into using SnapLogic is to anticipate a learning curve regarding the features currently available, as there are many ways to accomplish various tasks. It is best to take the training and engage with others who use SnapLogic to gather insights on achieving different functionalities since there is always room for improvement. I would rate this product an eight out of ten.

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 involves replacing old ETL functions, improving data flow, and enhancing efficiencies, business processes, and data quality across the enterprise.

A specific example of how I am using SnapLogic to improve a particular business process or data flow is that we have been able to go directly to subject matter experts and, through complete requirements-based discovery, rebuild, replace, and improve entire business functions very simply, quickly, and in ways that we were not previously able to do. Some functions that had been static and out of date for three, four, five years have been able to be turned around completely within a matter of weeks. The entire previous ETL architecture has been replaced within 12 months from when we started.

It is very easy to adapt to SnapLogic. It is very user-friendly. People who have not used the product with previous experience of any kind have been able to pick up and deliver most of this internally within the last year. While we have had a lot of external help from SnapLogic themselves, it has been a revelation compared to older, legacy ETL functions.

The best features SnapLogic offers include its ability to connect to almost anything. It has snaps for any function that you want to do with the data on the way in, which means we do not have to limit what our users want the requirements to include based on technical limitations, and we are able to work really quickly.

The ability to connect broadly and work fast has changed the way my teams operate by allowing us to unify a lot of data more easily without manual intervention, which previously took dozens of hours a week from certain staff members. Regardless of format, location, and means of accessing data, everything can be brought in by SnapLogic with as little manual data processing as we would like it to be. While we try to retain a human in the loop, we have significantly reduced the amount of manual labor for almost every integration.

SnapLogic has positively impacted my organization by costing a lot less than our previous ETLs, saving about 50 percent of our running costs without having done anything, just by using SnapLogic. We are able to engage with people and make promises that we can keep, and we can mitigate a lot of risk knowing that the functionality of the tool allows us not to have to worry about whether or not we can solve problems. We delivered more in the last year than what was previously deliverable in the last three or four years, and we have completely mitigated the risks of a failing and out-of-service ETL being used for primary data migration functions at the organization. Thus, we see risk mitigation, cost-cutting, and process improvements across the board, and most of these are very tangible to those who are subject matter experts in the areas we work with.

I see very few areas where SnapLogic needs improvement. There are some very fringe cases we have had to abandon due to minor complexity and time pressures, such as the ability to read a PDF and isolate tagged data areas on that PDF to extract data, which we did not find very easy to start with. However, we had the limitation of needing to turn this around in a matter of days, so we did not have time to investigate further. Other than that, I find it very difficult to identify areas for improvement; I think it is pretty industry-leading as far as these tools go. Comparing it to other products, I believe the return on investment has been met within a year and then some, whereas previously we wasted a lot of money trying to deliver the same things. Therefore, I have no real notes at this point, but I think consistent evolution is essential, and I look forward to seeing what they do next.

Support has been exemplary.

I have been using SnapLogic for 13 months.

SnapLogic is extremely stable.

SnapLogic's scalability is extremely reliable. We have built solutions that we have expanded to deliver higher volumes of data with the same pipelines, and we are able to iterate and expand on existing pipelines to deliver new functionality through simple Jira tickets without reinventing the wheel or starting whole projects to deliver change. Its self-documenting nature allows us to understand what was previously built and how to improve on it. The ability for us to refer back to the requirements we established through our recent work with SnapLogic strengthens the connection between the business processes and SnapLogic's role in allowing us to see the whole picture when looking at scaling.

Customer support is outstanding across all levels, including marketing, account management, and technical support, which are each individually and separately brilliant.

I previously used a different solution, initially Scribe, which reached end of life. We tried to use Talend, which did not meet our requirements. It was far too complex and lacked the user-friendly nature we needed; we relied on external developers to build our pipelines, adding significant extra costs on top of maintenance expenses. Therefore, when looking at cost savings, it must also include the amount we do not spend on external developers, which was substantial.

While we have had a lot of external help from SnapLogic themselves, it has been a revelation compared to older, legacy ETL functions.

I have shared some relevant metrics indicating that our previous ETL functions totaled around 120,000 pounds of commitment every year, while our SnapLogic commitment is less than half of that, providing an immediate return on investment. The pipeline function has also removed a lot of manual effort required, and while it has not reduced the number of employees we want to keep, it has allowed those employees to work on things that are more meaningful to the organization.

My company evaluated other options before choosing SnapLogic, but I do not know which ones since it occurred prior to my engagement with SnapLogic. However, I know that there were very few competitive alternatives that delivered anything close to what SnapLogic does.

My advice to others looking into using SnapLogic is to ensure that you upskill, train, and identify members of internal staff who can be used as developers on the product. The usability of SnapLogic far exceeds that of other products, which allows you to save a lot of money by using internal people along with the support and onboarding that SnapLogic provides. We did this with a few people, and it would have been better for us to do it with more internal staff because trusting them to take on development responsibilities is a great opportunity for upskilling, career development, and reducing development costs. I also recommend understanding as much of your existing environment and what can be replaced quickly before implementation to enable rapid wins and quick returns on investment.

Regarding SnapLogic's AI capabilities, I think its governance and security are areas I am not particularly close to in my day-to-day. The assurances and introductions we have been given make the trust in that very reliable. We make small use of AI in the SnapGPT snap functionality as well as in giving guidance on how to build pipelines, but we have not yet accessed larger-scale AI utilization. Thus, it has become less relevant than we expected immediately, but this may be something to engage with in the future. Therefore, I do not really have much to say about it, except that it seems reliable, and there is no reason not to trust it.

Regarding SnapLogic's AI capabilities, the accuracy and reliability of output, especially with features such as SnapGPT or pipeline guidance, in the small cases we have used it, have been reliable in almost every instance. I think as we deliver more complex work in the future that I cannot yet comment on, it may become something where I need to give more detail, but at this point, I think it is great.

SnapLogic is deployed in our organization using the cloud. I am not exactly sure which type because I was not involved in the implementation, but we access SnapLogic through the portal and have several snap engines running to deliver the work we are doing. Another member of my team who will be giving this review will be able to contribute more on this area.

I was not directly involved with the pricing, setup cost, and licensing, but I am, as the enterprise architect, the owner of all comparative data of cost and licenses and contracts we have across our ETL tools. SnapLogic is very competitive, and we found the bespoke and charity discounted options available extremely generous and suitable for our needs.

I would rate this review a 10 out of 10.

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 serves as our primary ETL tool to replace legacy ETL tools and move data through our systems. Processing events data is our best example, where event information comes from third-party platforms that we need to incorporate into our internal data ecosystem.

SnapLogic has led to faster delivery of many pipelines that previously would have taken much more time to develop. Our organization can now process data faster and engage in many more business value-added activities that follow after importing data into our ecosystem.

SnapLogic has halved our pipeline delivery time. Given that we have fewer technical team members who are able to develop, this has been a really beneficial saving.

SnapLogic is very adaptable, and the best features are the Snap Packs that come included, the patterns, and the knowledge base, which allow us to quickly build ETL flows with all of the tools at our disposal.

These features have made everything significantly easier and smoother because we have templates to start developing standard pipelines. This creates a sense of reusability, allowing us to develop our own patterns and apply them. For instance, something that works for one third-party events platform but may require slight customization for another can be easily copied and tweaked to integrate a different source platform.

The AI Snap GPT function within SnapLogic has been really beneficial. It has allowed some of our developers who are relatively new to the tool to cut down their learning time and address the learning curve with the product.

More native support, particularly around the Agent Creator AI agent tool, would be beneficial. Expanding to have native Anthropic support would be beneficial for our organization specifically.

More native support for other large-scale LLMs such as Anthropic would be helpful. Additionally, more training to address the learning curve would be valuable. However, there is a good amount of information in the knowledge base, and Snap GPT has been extremely beneficial.

We have been using SnapLogic since the start of 2025.

SnapLogic itself has relatively good capabilities and output. Sometimes it does take a little time to learn exactly how to ask Snap GPT to get the right response, but this comes quite naturally after some trial and error.

SnapLogic is very scalable. We have been experimenting with broadening its use case and delivering an increasing level of jobs and concurrent pipelines, and none of these have faced any performance or reliability bottlenecks.

Customer service from SnapLogic has been excellent.

We previously used a solution called Scribe, which is an ETL tool that is no longer under maintenance support, and this was one of the reasons why we needed to switch.

We looked at the incumbent, Scribe, and we also evaluated Power Automate, but that did not solve all of our problems. We also looked at Talend, but the pricing was a limiting factor.

SnapLogic is a highly scalable, adaptive, and forward-thinking solution, particularly if AI agents is something you wish to develop. You can be certain that you will get a responsive customer support experience with a knowledgeable group who are very proactive about solving your business use cases. The flexibility of SnapLogic should broadly cover many use cases. I would rate this solution a 9 out of 10.