We performed a comparison between SnapLogic and SSIS based on real PeerSpot user reviews.
Find out in this report how the two Data Integration solutions compare in terms of features, pricing, service and support, easy of deployment, and ROI."You can use other languages, such as Python, and easily connect to other systems."
"It is a stable solution."
"What I found most valuable in SnapLogic is the ETL feature, particularly the Transform Snap Pack, for example, any kind of reading or writing on Transform Snaps. Other than that, all the third-party connectivity tools such as the SAP Snap Pack, Salesforce Snap Pack, Workday Snap Pack, even the ServiceNow Snap Pack, I find all those are pretty useful in SnapLogic."
"The solutions ability to connect "snaps" or components to the graphic user interface is very intuitive, prevents errors, and makes implementations easy."
"I found SnapLogic valuable and what I found most valuable about it was its ETL feature. I also found its automation feature valuable. It can be used for automating manual activities. It can be used as a middleware for certain transactional data processing and minimal datasets and ETL activities."
"The API architecture makes it easy for orchestration."
"The connection with SOAP is the best feature."
"The product is easy to use and has many connectivity options."
"The initial setup was easy."
"The workflow features have been very valuable. You can have automated workflows and all the steps are controlled. The workflow functionality of integration services is excellent."
"SSIS integrates well with SQL servers and Microsoft products."
"The most valuables features are the relatively short learning curve, and the automation capabilities provided through the BIML add-in for SSDT."
"It has the ability to be deployed into the cloud through Data Factory, and run completely as a software as a service in the cloud."
"You can get data from any data source with SSIS and dump it to any outside source. It is helpful. Getting, extracting, converting, and dumping data doesn't require much effort because we can do everything in the user interface. You drag and drop, then give the required input. It's intuitive."
"The most valuable feature of SSIS is that it can handle real complex transformations."
"The interface is very user-friendly."
"One of the areas for improvement in SnapLogic is that the connectors for some of the applications should be more available in terms of testing in the dev environment. Another area for improvement is that the logging should be standardized, for example, the integration with an ELK stack should be required out-of-the-box, so you can ship the log and have it in the ELK stack. There should be integration with ELK stack for the log shipping."
"What could be improved in SnapLogic is that it was not capable in terms of processing a large number of datasets, but at that point, SnapLogic was evolving. It didn't give a lot of Snaps. I heard recently there are a lot of Snaps getting added and the solution was being enhanced, particularly to connect different data sources. When I was working with SnapLogic six months to one year back, I faced the issue of it not being capable of handling a huge volume of datasets or didn't have much of Snaps, and that was the drawback. If there is any large number of data sets, that's based on or depends on your configuration. If it is a huge volume of data, other traditional ETL tools such as Informatica and Talend can process millions and billions of records, while in SnapLogic, the Snaplex fails or it returns an error in terms of processing that huge volume of data. Informatica, Talend, or any other ETL tool can run for hours in terms of jobs, while SnapLogic jobs fail when the threshold is reached. SnapLogic isn't able to withstand processing, but I don't know if that's still an issue at present, because the solution is getting enhanced and it's been more than six months to one year since I last worked with SnapLogic. There are now a lot of Snaps getting added to the solution, and if it can overcome the limitations I mentioned, SnapLogic could be the go-to tool because currently, it's not being used as much in organizations. It's being used comparatively less compared to other retail tools."
"They should expand in terms of features for SaaS-based market requirements in different sectors."
"I would like to see more performance-related dashboards, ones that display the cost of a pipeline, for instance. Also, it would be helpful to have management dashboards for overseeing pipelines and connections."
"I am looking for more scheduling options. When it comes to scheduling, there are different tools in the market."
"There is room for improvement with APM management and how task execution looks."
"Ultra Pipelines provides real-time ingestion but it needs some adjustment."
"SnapLogic doesn't provide any on-premises software, so users have only cloud-based software to use."
"There is connectivity with other databases, however, this is the most significant issue that has to be addressed."
"We're in the process of switching to Informatica, and we need to work out data lineage and data profiling and to improve the quality of our data. SSIS, however, is not that compatible with Informatica. We managed to connect it to Informatica Metadata Manager, but we don't get good lineage, so we have to redo all our ETLs using the Informatica process in order to accept the proper data lineage."
"It would be nice if you could run SSIS on other environments besides Windows."
"SSIS is cumbersome despite its drag-and-drop functionality. For example, let's say I have 50 tables with 30 columns. You need to set a data type for each column and table. That's around 1,500 objects. It gets unwieldy adding validation for every column. Previously, SSIS automatically detected the data type, but I think they removed this feature. It would automatically detect if it's an integer, primary key, or foreign key column. You had fewer problems building the model."
"Future releases should improve the data lineage, as it currently is not good."
"The solution could improve by having quicker release updates."
"We'd like more integration capabilities."
"A change in the metadata source cripples the whole ETL process, requiring each module to be manually reopened."
SnapLogic is ranked 14th in Data Integration with 21 reviews while SSIS is ranked 2nd in Data Integration with 69 reviews. SnapLogic is rated 8.0, while SSIS is rated 7.6. The top reviewer of SnapLogic writes "Easy to set up, easy to use, and is low-code". On the other hand, the top reviewer of SSIS writes "Maintaining the solution and contacting its support team is easy". SnapLogic is most compared with AWS Glue, IBM InfoSphere DataStage, Azure Data Factory, Informatica Cloud Data Integration and Alteryx Designer, whereas SSIS is most compared with Informatica PowerCenter, Talend Open Studio, IBM InfoSphere DataStage, Oracle Data Integrator (ODI) and Boomi iPaaS. See our SSIS vs. SnapLogic report.
See our list of best Data Integration vendors and best Cloud Data Integration vendors.
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Snaplogic
I've found Matillion to be very intuitive and easy to use...
I wish I could answer that question, but my expertise is limited to SSIS only.
As far as I know 'talend' could be a better choice compare to the other tools.
you can address your question to our SAP department solutions@jet-bi.com
Informatica is the way forward
it depends on the infrastructure you are using and what's the total cost of ownership being authorized for the implementation. You can see the "Data Integration" partners within AWS-Redshift in the below link-
aws.amazon.com
Informatica undoubtedly is one of the best in the list. It's a great ETL tool but surely expensive in License.
Microsoft's SSIS is a light weight tool but not as robust as Informatica. Certain other software's like Talend and Matillion are also good. Talend has an open source option where developers can build their own APIs and then productionize those APIs and that's cost effective as well.
Traditionally SQL is a plus, automation is only by a ETL is smarter.
Any ETL tool that moves data to it's own server for processing will add overhead and will not use Redshift's power ( more specifically parallelism). It is recommended to use standard SQL for data processing.