Matillion ETL vs SAP Data Hub comparison

"The solution's most valuable feature is the CDC (Change Data Capture) component."

"The simplicity of this tool is nice. It has a good graphical user interface. You can also do a lot of generic stuff in the tool. If there is good connectivity to a cloud database, such as Snowflake, and you can have a lot of Snowflake functionality in the tool."

"It takes less than five minutes to set up and delivers results. It is much quicker than traditional ETL technologies."

"It has good integrations with Amazon Redshift and other AWS services."

"The technical support treats us well. They already have a support portal, and they are responsive, which helps."

"It's highly scalable. It takes upon itself the Redshift scalability, so it's very good."

"The most valuable feature of Matillion ETL is its ease of use. If you have had some experience with other solutions, such as Snowflake, the use of this solution will be simple."

"The loading of data is the most valuable feature of Matillion ETL."

"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."

"The most valuable feature is the S/4HANA 1909 On-Premise"

"SAP is one of the most seamless ERPs that have integrated SAP archiving within Excel. I have not seen this with any other database."

"Ideally, I would like it to integrate with Secrets Manager as well as the AWS."

"The product's scalability needs improvement. Perhaps adding more connectors would be beneficial."

"The current version is a bit more limited because it's on a virtual machine, and everything executes on that one virtual machine."

"The cost of the solution is high and could be reduced."

"In the next release, we would like to have connections to more databases."

"It can have multi-environment support. We should be able to deploy it in different environments. Its integration with SAP connection is not so nice, which should be improved. It can also support an on-prem database."

"When using the SQL loader type there were not a lot of pre-processing features for the data. For example, if there is a table with twenty columns, but we only want to load ten columns. In that case, we can use a security script to select the specific columns needed. However, if we want to perform extensive pre-processing of the data, I faced some challenges with Matillion ETL. I did not encounter many challenges, but my overall experience is limited as I only have three years of experience."

"It needs integration with more data sources."

"Nowadays there are some inconsistencies in data bases, however, they upgrade and release the versions to market."

"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."

"It is not necessarily a cheap solution. However, it's reasonable priced, especially with the smaller machines that we run it on."

"The AWS pricing and licensing are a cost-effective solution for data integration needs."

"I think it is cost conscious. It used to be very cheap and they have more recently bumped up the pricing, so it is competitive now."

"A rough estimation of the cost is around 20,000 dollars a month, however, this is dependent on the machine used and how Matillion ETL is used."

"It is cost-effective. Based on our use case, it's efficient and cheap. It saves a lot of money and our upfront costs are less."

"The product must improve its pricing."

"The pricing depends on what edition the customer opts for. For example, the standard edition is priced at $2.00 per credit. And you are only charged when you use it. You're not charged when it's idle."

"Matillion ETL has a pay-as-you-go pricing model of a few dollars per hour of runtime."

"The Cloud is very expensive, but SAP HANA previous service is okay."