SnapLogic is the Agentic Integration Company, integrating AI, data, applications, and microservices into one powerful platform that transforms how enterprises connect, automate, and scale. Unlike legacy integration tools, SnapLogic is built for the AI era and trusted by global leaders, including AstraZeneca, Adobe, Verizon, and Sony. With its industry-leading platform, SnapLogic empowers every team across the enterprise to securely integrate applications, automate business processes, and orchestrate agentic workflows at scale. SnapGPT, an AI copilot built into the platform, enables any user to describe an integration in plain language and have it built automatically, reducing dependency on specialist engineering resources.
The SnapLogic Platform is a leading iPaaS that empowers business and IT teams to quickly and intuitively move data to and from Amazon Redshift, surfacing critical business insights that drive better decisions. Teams are also empowered to create custom integrations that enable automated business processes. SnapLogic is devoted to making data migration, data warehousing, and data integration easy, intuitive, and fast.
With SnapLogic's Amazon Redshift Snap Packs, users can create and manage Redshift integration pipelines via drag-and-drop and AI-assisted recommendation logic. Our AI-powered integration platform improves developer productivity by 15%. In addition to the 14 Redshift Snaps, we offer over 1,000 Snaps to connect different data sources, including on-premise apps like ERPs, SaaS apps, and mobile and device data. SnapLogic has over 100 Amazon Redshift customers, including Adobe, AstraZeneca, HBO, Sony, Workday, Ikea, Stanford, EERO, Kaplan, and Asana. Use Cases where we have been successful include data integration to Redshift, S3, DynamoDB, and SQS, and migrating up to petabytes of data into our customers' Redshift environments.
The SnapLogic Agentic Integration Platform simplifies onboarding for customers of Amazon Redshift, DynamoDB, SQS, and Relational Database Service (RDS). With SnapLogic, customers move data in and out of Redshift, DynamoDB, SQS, and RDS at any latency (batch, real-time, and via triggers). Find SnapLogic on the AWS Marketplace and learn more about our Professional Services Packages.
SnapLogic also supports cloud data warehouses and data lakes. Plus, intelligent connectors called Snaps are available for 1,000+ different cloud and on-premises data sources and applications such as Salesforce, Microsoft SQL Server, Workday, IBM DB2, PostgreSQL, SAP, Teradata, NetSuite, and Netezza.
SnapLogic also has a Sagemaker reference architecture. SnapLogic uses Sagemaker to help build SnapLogic, where customers can benefit from our combined years of AI/ML experience. The SnapLogic Platform is purpose-built for the AI era. SnapGPT, a built-in AI copilot, enables business users and integration specialists alike to build pipelines, automate processes, and orchestrate workflows using natural language. AgentCreator builds on this, allowing teams to design, deploy, and manage AI agents that operate autonomously across enterprise systems. With native MCP support, those agents can securely connect to any MCP-compatible tool or data source, making SnapLogic a foundational layer for enterprise AI infrastructure.
SnapLogic customers process >960B transactions per month into Redshift, increasing AWS revenue via consumption.
Forrester reveals a customer ROI of 181% and total benefits of over $3.3 million over three years for the SnapLogic platform.
SnapLogic's agentic integration platform enables 35% of integration hours to transfer to citizen integrators and improves efficiency for core SnapLogic data engineers and developers by 15%.
AWS Marketplace now accepts line of credit payments through the PNC Vendor Finance program. This program is available to select AWS customers in the US, excluding NV, NC, ND, TN, & VT.
Pricing is based on the duration and terms of your contract with the vendor. This entitles you to a specified quantity of use for the contract duration. If you choose not to renew or replace your contract before it ends, access to these entitlements will expire.
Additional AWS infrastructure costs may apply. Use the AWS Pricing Calculator to estimate your infrastructure costs.
This listing bills through contracts priced in units. You start with the SnapLogic Platform, the base data and application integration platform. Three add-ons extend it for specific needs. IIP for Amazon Connect adds contact-center integration. IIP for Higher Education targets education workflows. The Snaplogic Mainframe Accelerator uses AI to connect mainframe systems and load data into a cloud data warehouse. Each dimension is sold in units, so you scale by adjusting unit quantity. The add-ons are independent options layered on the platform rather than tiers you upgrade between.
Top-of-mind questions for buyers
What counts as one unit for the SnapLogic Platform and its add-ons?
Each dimension is priced in units, and unit definitions depend on the endpoints and connectors you configure. You choose the data and application endpoints you want to connect. Pricing follows a package approach tied to those connections rather than to data volume, since data movement, pipelines, and transformations are unlimited.
Does my bill change as I move more data or add more pipelines?
No. Data movement, pipelines, and transformations are unlimited at the same price. You can create as many connections to an endpoint as you need. Cost changes when you adjust the unit quantity or add connectors, not when data volume grows. Deploying on GroundPlex or CloudPlex does not change the price.
How do the three add-ons combine with the base SnapLogic Platform on my invoice?
The SnapLogic Platform is the base you start with. IIP for Amazon Connect, IIP for Higher Education, and the Mainframe Accelerator are independent add-ons layered on top. You buy only the ones you need in units. Each bills separately alongside the platform rather than replacing it.
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SnapGPT AI copilot enables users to describe integrations in plain language for automatic pipeline construction, and AgentCreator allows design and deployment of autonomous AI agents across enterprise systems.
Multi-Source Data Connectivity
Over 1,000 intelligent connectors called Snaps available for cloud and on-premises data sources including Salesforce, SAP, Workday, IBM DB2, PostgreSQL, Teradata, NetSuite, and Redshift.
Drag-and-Drop Pipeline Management
Drag-and-drop interface with AI-assisted recommendation logic for creating and managing data integration pipelines, including 14 dedicated Redshift Snaps.
Multi-Latency Data Movement
Support for batch, real-time, and trigger-based data movement across AWS services including Redshift, DynamoDB, SQS, and RDS.
Native MCP Support for Agent Integration
Agents can securely connect to any MCP-compatible tool or data source, providing a foundational layer for enterprise AI infrastructure.
Codeless Visual Development Interface
Drag and drop visual UI enabling users to build data integrations without coding, with pre-built templates and integration wizards for accelerated development
Parallel Data Integration Architecture
Highly scalable parallel data integration architecture supporting both ETL and ELT patterns with pushdown optimization for maximum throughput and performance into Amazon Redshift
Multi-Source Connectivity
Native connectors supporting hundreds of applications and data sources across on-premises and cloud environments including AWS services (Redshift, S3, RDS, Aurora) and enterprise applications (Salesforce, Workday, Oracle, SAP, ServiceNow)
FedRAMP Compliance
FedRAMP authorization including Integration Base, Data Integration, and tiered connectors (Tier B, C, D) for government cloud deployments
Data Integration and Synchronization
Capabilities for data warehousing, data lake initiatives, and task flow orchestration with support for scheduling and automation of data synchronization across multiple sources and destinations
Agentic Automation
Autonomous AI agents that build, modify, and maintain production data pipelines across the delivery lifecycle
Schema Drift Detection
Automated detection and remediation workflows for schema changes in data pipelines
Git-Compatible Pipeline Output
Production-ready pipeline code that is compatible with Git version control and CI/CD practices
Integrated Data Lineage and Visibility
Built-in lineage tracking and operational visibility for monitoring data pipeline execution and dependencies
Pushdown SQL Architecture
SQL computation pushed to the data warehouse layer for optimized query execution and reduced data movement
Automation has reduced manual file transfers and now monitoring performance needs improvement
Reviewed on Sep 21, 2026
Review provided by PeerSpot
What is our primary use case?
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.
What is most valuable?
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.
What needs improvement?
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.
For how long have I used the solution?
I have been using SnapLogic for about two and a half years, the whole time I have been at Vitesse.
What do I think about the stability of the solution?
SnapLogic has been stable in my experience with no crashes.
What do I think about the scalability of the solution?
Regarding SnapLogic's scalability, we have not needed to scale it as it has been stable.
How are customer service and support?
The customer support for SnapLogic has been good as whenever we have raised an issue, I get a response within 24 hours.
Which solution did I use previously and why did I switch?
I did not previously use a different solution before SnapLogic, as SnapLogic was already in use at this company before I got here.
How was the initial setup?
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.
What was our ROI?
I have seen a return on investment with SnapLogic.
What other advice do I have?
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.
reviewer2901144
Integration workflows have reduced development time and now convert external data formats efficiently
Reviewed on Sep 21, 2026
Review provided by PeerSpot
What is our primary use case?
The main use case for using SnapLogic is to integrate external systems to Syndigo. For example, we have XML files that need to be converted into our Syndigo format to create entities in the Syndigo system.
What is most valuable?
The best features are that we can quickly consume the Snaps which are already available, so we don't need to write scalable code. We can quickly integrate our systems via SnapLogic Snaps, and that speeds up our integration process.
The pre-developed Snaps are really helpful for both non-developers and developers, and that reduces the time for integrations significantly.
Implementing the pipeline quickly, rather than developing code, has impacted us tremendously.
If we develop the same integration using any of the latest technology, it would take a minimum of one or two months. Using SnapLogic, we can develop the same logic via Snaps within two or three weeks, which provides tremendous time saving as well as cost reduction.
What needs improvement?
When we face errors in the existing scheduler run, we cannot trace the logs. Adding more logs in the existing Snaps could make it much easier to debug errors.
If more logs were added to the existing Snap, users could debug errors and view log information more effectively.
For how long have I used the solution?
I have been using SnapLogic for the last one year.
How are customer service and support?
Customer support is really good.
Which solution did I use previously and why did I switch?
Previously, we were using a private app via Java logic to integrate the system.
What was our ROI?
It has really saved our time when we are using SnapLogic integration systems.
Which other solutions did I evaluate?
We have not validated or evaluated any other options.
What other advice do I have?
SnapLogic AI capabilities have good potential, particularly with the integration and automation features.
The AI provides accurate and useful outputs, especially for common integrations.
SnapLogic is easy to learn because SnapLogic itself provides documentation for each individual Snap, making it easy to read and understand the existing Snaps.
When creating the scheduler, we provided email notifications for successful scheduler runs or failed scenarios, so whenever we receive the email notification, we go and check the monitoring tool to debug the failed scenario.
It is easy to connect with external systems via the existing Snaps, something like the 365 Snap or the API endpoint Snap.
The documentation provided by SnapLogic is really helpful, and it is all up-to-date information.
SnapLogic has a mapper Snap where we need to configure the mapping, and for simple and collection mapping as well as complex mapping transformation, there is an individual syntax to transfer the data.
We have created multiple users to provide them access only to specific project access.
SnapLogic processes a large amount of data within a shorter period of time and has good scalability for handling large integration data. I would rate this review 9 out of 10.
reviewer2900313
Parallel data migrations have accelerated complex API workflows and still need smarter AI design help
Reviewed on Sep 18, 2026
Review from a verified AWS customer
What is our primary use case?
My main use case for SnapLogic is data migration from databases to new systems using APIs or direct database-to-database transfers, as well as generating reports for various purposes.
A specific example of a migration I completed using SnapLogic involved moving data from SQL Server to a NextGen system that Ideagen currently owns. This migration was particularly interesting because it had many dependencies from within the incident module. Every time data was posted, it used a unique identifier that needed to be saved back into the database and then used again, which made the pipeline design quite complex.
What is most valuable?
One of the best features SnapLogic offers is the ability to use multiple parallel executions through the pool size setting on a Pipeline Execute Snap. Additionally, the error logging functionality in SnapLogic is excellent, and when used with cloud infrastructure, it can directly read .SLP files and trigger pipelines.
The parallel execution and error logging features have significantly helped my day-to-day work. In our migrations from SQL Server to a NextGen system using APIs, the API is single-threaded and requires only one request at a time in a first-in, first-out manner. However, by using SnapLogic with different pool sizes, I was able to execute multiple requests to the same server when the authentication was the same, such as using a bearer token. This capability reduced the overall pipeline execution time. When an API-level error occurred, the pipeline threw out an error indicating what the problem was, allowing me to capture the error details for debugging before reprocessing that particular document or instance.
SnapLogic has positively impacted my organization by providing diversity in connections and Snaps, and it is more developer-friendly when using a drag-and-drop tool.
Being developer-friendly and having diverse connections has significantly impacted my team and projects. This allows us to look up data from the live original server. When using multiple source systems, whether they be databases, CSV files, or any kind of file or REST Connect Get Snap, we can combine all of these into a single mapping and directly post it to a target source. This diversity of Snaps is particularly valuable when we have multiple sources in play.
What needs improvement?
SnapLogic can be improved by incorporating an AI system in the Expression Builder that learns from what has already been done in the current project, allowing for auto-suggestions.
Regarding SnapLogic's AI capabilities, I believe its governance and security are good, but the actual pipeline design is not production-ready. The accuracy and reliability of SnapLogic's AI output is around thirty to forty percent, with the remaining work needing to be completed by the developer. If vague instructions are provided, approximately ten to twenty percent of the work can be handled using SnapLogic's AI, but the remaining tasks should be completed through developer intervention.
For how long have I used the solution?
I have been using SnapLogic for around four years.
What do I think about the stability of the solution?
In my experience, SnapLogic is indeed stable.
What do I think about the scalability of the solution?
I would rate SnapLogic's scalability as eight out of ten.
How are customer service and support?
The customer support for SnapLogic received a rating of seven out of ten.
What other advice do I have?
My advice for others looking into using SnapLogic is that it is easy to learn, easy to code, and easy to develop. I would rate this review seven out of ten.
Which deployment model are you using for this solution?
Hybrid Cloud
If public cloud, private cloud, or hybrid cloud, which cloud provider do you use?
Amazon Web Services (AWS)
Ashish Simhadri
Low-code pipelines have accelerated complex data migrations and simplified large-scale batch loading
Reviewed on Sep 16, 2026
Review provided by PeerSpot
What is our primary use case?
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.
What is most valuable?
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.
What needs improvement?
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.
For how long have I used the solution?
I have been using SnapLogic for one and a half years on various multiple projects from the perspective of data migration and ingestions.
What do I think about the stability of the solution?
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.
What other advice do I have?
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.
reviewer2898921
Data integrations have simplified CRM imports and have removed legacy platform risks
Reviewed on Sep 15, 2026
Review from a verified AWS customer
What is our primary use case?
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.
What is most valuable?
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.
What needs improvement?
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.
For how long have I used the solution?
I have been using SnapLogic for 18 months.
What do I think about the stability of the solution?
SnapLogic has been reliable for me with no downtime or disruptions.
What do I think about the scalability of the solution?
SnapLogic's scalability as our needs grow or change is good.
How are customer service and support?
The customer support for SnapLogic is very good.
What was our ROI?
I do not have any specific outcomes or metrics to share regarding time or money saved or how my team's workload has changed.
What other advice do I have?
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.