

SnapLogic and AWS Glue compete in the data integration and ETL space. SnapLogic takes the upper hand in pricing and ease of use, while AWS Glue holds the advantage in integration and scalability within the AWS ecosystem.
Features: SnapLogic offers a visual drag-and-drop interface, an extensive library of connectors, and AI-enhanced low-code development for efficient pipeline design. AWS Glue provides a serverless architecture, data catalog capabilities, and deep integration with AWS services for expansive data processing.
Room for Improvement: SnapLogic could enhance its scalability options and expand the number of available prebuilt connectors. A more in-depth integration with other cloud ecosystems might also improve its offering. AWS Glue's interface could benefit from more intuitive design features, and its steep learning curve could be lessened with better onboarding options. Improvements in cost predictability would enhance user satisfaction.
Ease of Deployment and Customer Service: SnapLogic provides a straightforward cloud-based setup with responsive customer support, facilitating rapid deployment and adoption. AWS Glue's deployment can be complex due to deeper integration with AWS services, though it benefits from AWS's extensive customer service resources, requiring users to be familiar with the AWS environment.
Pricing and ROI: SnapLogic offers flexible pricing schemes suited for different business sizes, contributing to a quicker ROI through faster deployment. AWS Glue, while potentially costlier, justifies its price with a comprehensive set of features and scalability, often suited for businesses already embedded in the AWS ecosystem.
I advocate using Glue in such cases.
SnapLogic is really helpful and processes in very little time, so it doesn't take much time compared to any legacy tool.
The reports and pipelines run, leading to cost savings that reduce manual effort and save 50,000 to 150,000 USD annually.
It improved our productivity by fifteen percent and shifted work from IT to business users.
Upgrades occur every four months, and new developments coincide with version updates.
For complex Glue-related problems such as job failures or permission issues, their documentation is good, but having direct access to support helps cut down troubleshooting time significantly.
The responsiveness, technical expertise, knowledge base and documentation, support channels, and continuous improvement were impeccable.
The technical support from SnapLogic is excellent, and I would give it a complete ten.
Some SMEs are allotted for the organization, so in case of any issue, we have their email IDs to contact them for support, including SMEs and community.
It is beneficial to upgrade jobs, and we conduct extensive testing in development before migrating to production.
It can easily handle data from one terabyte to 100 terabytes or more, scaling nicely with larger datasets.
After implementing SnapLogic, pipelines that processed one to two million records per week can now handle five to 10 million records without additional infrastructure.
SnapLogic is very scalable, and it can be adjusted based on our requirements, considering the organization type and the data it produces.
SnapLogic is easily scalable.
AWS Glue is highly stable, and I would rate its stability as nine.
I would rate the stability of SnapLogic as nearly ten out of ten.
But recently, in a year, I haven't found many performance issues in SnapLogic.
Migrating jobs from version 3.0 to 4.0 can present compatibility issues.
With AWS, I gather data from multiple sources, clean it up, normalize it, de-duplicate it, and make it presentable.
A more user-friendly and simpler process would help speed up the deployment process.
We require a data pipeline that can be read without latency and without any delay.
Having more granular control and deeper insights into execution performance would really help.
If the AI capabilities and integrations were more intuitive and easy to learn for new users, it would be greatly beneficial.
Costing depends on resource usage, and cost optimization may involve redesigning jobs for flexibility.
AWS charges based on runtime, which can be quite pricey.
The smallest cost for a project is around €700, while the largest can reach up to €7,000 based on the scale of the usage.
In terms of setup cost, it is relatively low compared to traditional on-premises tools.
There would be only one point of improvement if the price could be lower.
SnapLogic is positioned at around seven or eight out of ten in terms of pricing.
For ETL, I feel the performance is excellent. If I create jobs in a standard way, the performance is great, and maintenance is also seamless.
AWS Glue's most valuable features include its transformation capabilities, which provide data quality and shape for processing in ML or AI models.
AWS Glue has reduced efforts by 60%, which is the main benefit.
I also like the whole child-parent pipeline feature; it allows me to break up a process into smaller pieces and then have one big pipeline that controls these smaller pipelines.
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.
SnapLogic excels in data transformations, monitoring, and observability, providing scalability controls for the pipelines.
| Product | Mindshare (%) |
|---|---|
| AWS Glue | 7.6% |
| SnapLogic | 3.3% |
| Other | 89.1% |
| Company Size | Count |
|---|---|
| Small Business | 11 |
| Midsize Enterprise | 6 |
| Large Enterprise | 32 |
| Company Size | Count |
|---|---|
| Small Business | 11 |
| Midsize Enterprise | 7 |
| Large Enterprise | 16 |
AWS Glue is a serverless data integration service offering seamless integration with AWS services like S3, Redshift, and Athena. Known for its flexibility with data formats and automation of ETL tasks, AWS Glue enhances data management and transformation.
AWS Glue facilitates seamless data extraction, transformation, and loading for businesses, integrating with key AWS services, allowing efficient data pipeline automation. It's valued for a user-friendly GUI, scalability, and cost-effectiveness, supporting PySpark for complex datasets and includes a robust data catalog, real-time backup capabilities, and code generation. Despite its strengths, improvements are needed in documentation, training, and broader programming language support. Users face challenges with its complex interface and integration with non-AWS products, driving demand for enhancements in its usability and performance.
What are AWS Glue's most important features?Businesses leverage AWS Glue in industries for ETL processes, data integration, and transformation. It is used to optimize data lakes or warehouses integration, enhancing data cataloging and real-time integration. Its serverless feature enables efficient data processing in sectors like finance and healthcare, where handling complex data-intensive tasks is crucial.
SnapLogic offers a flexible, low-code environment for data integration and automation, utilizing an intuitive drag-and-drop interface with pre-built components to streamline the integration of multiple systems like Salesforce, SAP, and Workday, optimizing workflow automation.
SnapLogic provides robust ETL capabilities and broad connectivity options, enabling custom script implementation. Its visual design supports seamless deployment and efficient error management. Users benefit from automating data flows and enhancing data consistency through API integrations while managing both synchronous and asynchronous processes. However, areas needing improvement include user-friendly integrations, API management, and dashboard functionalities, as well as better transparency and error debugging. There is a call for improved handling of large datasets, enhanced connectivity, and advanced monitoring, DevOps integration, and AI functionalities. Customer support and documentation could be more comprehensive, especially for intricate operations.
What are SnapLogic's key features?In industries like finance, healthcare, and logistics, SnapLogic is extensively implemented for ETL processes, data migration, and automating complex workflows to improve data accuracy and enhance operational efficiency. These capabilities allow organizations to streamline operations and focus on strategic initiatives.
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