We performed a comparison between Matillion ETL and SAP Data Hub based on real PeerSpot user reviews.
Find out what your peers are saying about Amazon Web Services (AWS), MuleSoft, Matillion and others in Cloud Data Integration."The most valuable feature of Matillion ETL is the ETL. The solution is open-source which provides advantages, such as good performance and high efficiency. Additionally, it supports three data types which eliminates predefining the data, and we can write script models in Python."
"It has improved the costs of managing my customer’s data."
"The tool's middle-dimensional structure significantly simplifies obtaining the right data at the appropriate level. This feature makes deploying our applications easier since we utilize a single source without publishing data from various sources."
"It is an incredibly user-friendly and intuitive tool, making the learning curve quite smooth"
"The loading of data is the most valuable feature of Matillion ETL."
"It takes less than five minutes to set up and delivers results. It is much quicker than traditional ETL technologies."
"Matillion ETL is one hundred percent stable."
"It can scale to a great extent. It can handle the load that we are putting on it, which is about 5TBs."
"The most valuable feature is the S/4HANA 1909 On-Premise"
"Its connection to on-premise products is the most valuable. We mostly use the on-premise connection, which is seamless. This is what we prefer in this solution over other solutions. We are using it the most for the orchestration where the data is coming from different categories. Its other features are very much similar to what they are giving us in open source. Their push-down approach is the most advantageous, where they push most of the processing on to the same data source. This means that they have a serverless kind of thing, and they don't process the data inside a product such as Data Hub. They process the data from where the data is coming out. If it is coming from HANA, to capture the data or process it for analytics, orchestration, or management, they go to the HANA database and give it out. They don't process it on Data Hub. This push-down approach increases the processing speed a little bit because the data is processed where it is sitting. That's the best part and an advantage. I have used another product where they used to capture the data first and then they used to process it and give it. In Data Hub, it is in reverse. They process it first and give it, and then they put their own manipulations. They lead in terms of business functions. No other solution has business functions already implemented to perform business analysis. They have a lot of prebuilt business functions for machine learning and orchestration, which we can use directly to get an analysis out from the existing data. Most of the data is sitting as enterprise data there. That's a major advantage that they have."
"SAP is one of the most seamless ERPs that have integrated SAP archiving within Excel. I have not seen this with any other database."
"Performance can be improved for efficiency, and it can be made faster."
"There are certain functions that are available in other ETL tools which are still not present in Matillion ETL. It would be good to have more features."
"To complete the pipeline, they might want to include some connectors which would put the data into different platforms. This would be helpful."
"While the UI is good, it could be improved in its efficiency and made easier to use."
"The product must enhance its near-real-time data capture feature."
"I found some of the more complex aspects of ETL challenging, but I grasped the concepts fairly quickly."
"One of the features that's in development is data privacy in the cloud, along with further SAP integration. For connectivity to SAP systems."
"It needs integration with more data sources."
"In 2018, connecting it to outside sources, such as IoT products or IoT-enabled big data Hadoop, was a little complex. It was not smooth at the beginning. It was unstable. It took a lot of time for the initial data load. Sometimes, the connection broke, and we had to restart the process, which was a major issue, but they might have improved it now. It is very smooth with SAP HANA on-premise system, SAP Cloud Platform, and SAP Analytics Cloud. It could be because these are their own products, and they know how to integrate them. With Hadoop, they might have used open-source technologies, and that's why it was breaking at that time. They are providing less embedded integration because they want us to use their other products. For example, they don't want to go and remove SAP Analytics Cloud and put everything in Data Hub. They want us to use SAP Analytics Cloud somewhere else and not inside the Data Hub. On the integration part, it lacks real-time analytics, and it is slow. They should embed the SAP Analytics Cloud inside Data Hub or support some kind of analysis. They do provide some analysis, but it is not extensive. They are moreover open source. So, we need a lot of developers or data scientists to go in and implement Python algorithms. It would be better if they can provide their own existing algorithms and give some connections and drop-down menus to go and just configure those. It will make things really quick by increasing the embedded integrations. It will also improve the process efficiency and processing power. Its performance needs improvement. It is a little slow. It is not the best in the market, and there are other products that are much better than this. In terms of technology and performance, it is a little slow as compared to Microsoft and other data orchestration products. I haven't used other products, but I have read about those products, their settings, and the milliseconds that they do. In Azure Purview, they say that they can copy, manage, or transform the data within milliseconds. They say that they can transform 100 gigabytes of data within three to five seconds, which is something SAP cannot do. It generally takes a lot of time to process that much amount of data. However, I have never tested out Azure."
"The company has everything offshore."
"Nowadays there are some inconsistencies in data bases, however, they upgrade and release the versions to market."
Matillion ETL is ranked 4th in Cloud Data Integration with 24 reviews while SAP Data Hub is ranked 25th in Data Governance with 3 reviews. Matillion ETL is rated 8.6, while SAP Data Hub is rated 7.6. The top reviewer of Matillion ETL writes "Efficient data integration and transformation with seamless cloud-native integration". On the other hand, the top reviewer of SAP Data Hub writes "The solution is seamless, but the database sometimes leads to confusion". Matillion ETL is most compared with Snowflake, Azure Data Factory, AWS Glue, Informatica PowerCenter and SSIS, whereas SAP Data Hub is most compared with Microsoft Purview, SAP Data Services, Alation Data Catalog, Azure Data Factory and Palantir Foundry.
We monitor all Cloud Data Integration reviews to prevent fraudulent reviews and keep review quality high. We do not post reviews by company employees or direct competitors. We validate each review for authenticity via cross-reference with LinkedIn, and personal follow-up with the reviewer when necessary.
