SAP IQ and Snowflake are leading products in the data warehousing and business intelligence category. Snowflake seems to have the upper hand due to its real-time scalability and cloud-native architecture.
Features: SAP IQ is known for handling large structured data with column-based compression and high query speed, and it uses a patented index for enhanced performance. Snowflake offers real-time scalability, an intuitive interface, and supports multiple data formats in its cloud-native architecture, providing significant speed and flexibility.
Room for Improvement: SAP IQ needs better system support, improved integration with Hadoop, and enhanced backup management. Pricing complexity remains a concern. Snowflake is perceived as expensive and could improve cost transparency, machine learning support, and integration with other tools. Enhancements to stored procedures and its user interface for data extraction are also noted.
Ease of Deployment and Customer Service: SAP IQ is primarily deployed on-premises, limiting flexibility, and its support services face criticism for delays. Snowflake, with its wide cloud deployment options, provides ease of deployment and is praised for its reliable 24/7 global customer support model, enhancing its appeal to businesses.
Pricing and ROI: SAP IQ users find it cost-effective with negotiable licensing options, despite concerns over add-on costs. Snowflake's pay-as-you-go model bases costs on data storage and processing usage. While some users find this model fair, others view it as costly compared to competitors, necessitating careful management of the pricing structure.
I received great support in migrating data to Snowflake, with quick responses and innovative solutions.
The technical support from Snowflake is very good, nice, and efficient.
The billing doubles with size increase, but processing does not necessarily speed up accordingly.
Snowflake is very scalable and has a dedicated team constantly improving the product.
Snowflake is very stable, especially when used with AWS.
Snowflake as a SaaS offering means that maintenance isn't an issue for me.
Enhancements in user experience for data observability and quality checks would be beneficial, as these tasks currently require SQL coding, which might be challenging for some users.
Cost reduction is one area I would like Snowflake to improve.
Snowflake's pricing is on the higher side.
Snowflake lacks transparency in estimating resource usage.
Snowflake is a data lake on the cloud where all processing happens in memory, resulting in very fast query responses.
The independence of the compute and storage within Snowflake is key.
SAP® IQ software delivers speed and power for extreme-scale enterprise data warehousing and analytics. Its column-oriented, grid-based massively parallel processing (MPP) architecture and patented data compression and indexing technologies enable companies to exploit the value of huge amounts of data at the speed of business.
Snowflake is a cloud-based data warehousing solution for storing and processing data, generating reports and dashboards, and as a BI reporting source. It is used for optimizing costs and using financial data, as well as for migrating data from on-premises to the cloud. The solution is often used as a centralized data warehouse, combining data from multiple sources.
Snowflake has helped organizations improve query performance, store and process JSON and XML, consolidate multiple databases into one unified table, power company-wide dashboards, increase productivity, reduce processing time, and have easy maintenance with good technical support.
Its platform is made up of three components:
Snowflake has many valuable vital features. Some of the most useful ones include:
There are many benefits to implementing Snowflake. It helps optimize costs, reduce downtime, improve operational efficiency, and automate data replication for fast recovery, and it is built for high reliability and availability.
Below are quotes from interviews we conducted with users currently using the Snowflake solution:
Sreenivasan R., Director of Data Architecture and Engineering at Decision Minds, says, "Data sharing is a good feature. It is a majorly used feature. The elastic computing is another big feature. Separating computing and storage gives you flexibility. It doesn't require much DBA involvement because it doesn't need any performance tuning. We are not doing any performance tuning, and the entire burden of performance and SQL tuning is on Snowflake. Its usability is very good. I don't need to ramp up any user, and its onboarding is easier. You just onboard the user, and you are done with it. There are simple SQL and UI, and people are able to use this solution easily. Ease of use is a big thing in Snowflake."
A director of business operations at a logistics company mentions, "It requires no maintenance on our part. They handle all that. The speed is phenomenal. The pricing isn't really anything more than what you would be paying for a SQL server license or another tool to execute the same thing. We have zero maintenance on our side to do anything and the speed at which it performs queries and loads the data is amazing. It handles unstructured data extremely well, too. So, if the data is in a JSON array or an XML, it handles that super well."
A Solution Architect at a wholesaler/distributor comments, "The ability to share the data and the ability to scale up and down easily are the most valuable features. The concept of data sharing and data plumbing made it very easy to provide and share data. The ability to refresh your Dev or QA just by doing a clone is also valuable. It has the dynamic scale up and scale down feature. Development and deployment are much easier as compared to other platforms where you have to go through a lot of stuff. With a tool like DBT, you can do modeling and transformation within a single tool and deploy to Snowflake. It provides continuous deployment and continuous integration abilities. There is a separation of storage and compute, so you only get charged for your usage. You only pay for what you use. When we share the data downstream with business partners, we can specifically create compute for them, and we can charge back the business."
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