

SAP IQ and Snowflake compete in the data warehousing category. Snowflake seems to have the upper hand due to its cloud-native approach and dynamic scalability, while SAP IQ excels in data compression and transaction performance.
Features: SAP IQ offers exceptional query performance through its columnar storage and patented indices. It provides high data compression, reducing 100GB to about 20GB, and supports high concurrency. Snowflake supports dynamic scalability and a flexible architecture, ideal for varying workloads, with features like time travel and zero copy cloning for cloud-native data warehousing.
Room for Improvement: SAP IQ needs better concurrency management, error messaging, and enhanced marketing and support. Its backup support also requires improvement. Snowflake could improve its documentation, ETL capabilities, and machine learning support, while better integration with other systems and pricing transparency are desired.
Ease of Deployment and Customer Service: SAP IQ is primarily on-premises, which limits scalability, and its customer service is mixed. In contrast, Snowflake thrives in public and hybrid cloud environments, offering ease of deployment and responsive global customer service, benefiting from cloud-based options.
Pricing and ROI: SAP IQ uses fixed licensing with additional costs for features like partitioning. It is economical for high performance but poses challenges in cost predictability. Snowflake's consumption-based model is flexible but can seem higher due to its pay-as-you-go approach. Its credit-based system aids in cost management, offering better scalability benefits and cost-effectiveness.
It seems very difficult to get proper advanced assistance on advanced or complicated problems.
The quality of support from SAP is very good; if it's a known problem, they will have a knowledge base, so we will get immediate assistance.
I received great support in migrating data to Snowflake, with quick responses and innovative solutions.
I am satisfied with the work of technical support from Snowflake; they are responsive and helpful.
The technical support from Snowflake is very good, nice, and efficient.
SAP IQ is actually quite effective when it comes to scalability.
We can span the read and write load into multiple nodes, and that scalability is there.
Snowflake is very scalable and has a dedicated team constantly improving the product.
The billing doubles with size increase, but processing does not necessarily speed up accordingly.
Recently, Snowflake has introduced streaming capabilities, real-time and dynamic tables, along with various connectors.
It's usually something external, such as lack of disk space or problems arising from the integration to other systems.
Snowflake is very stable, especially when used with AWS.
Snowflake as a SaaS offering means that maintenance isn't an issue for me.
When there is an issue, the error messaging we get is not always sufficient to do a fast and solid fix.
It is easy to deploy SAP IQ; the implementation and installation are easy.
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.
What things you are going with to ask the support and how we manage the relationship matters a lot.
If more connectors were brought in and more visibility features were added, particularly around cost tracking in the FinOps area, it would be beneficial.
Snowflake's pricing is on the higher side.
Snowflake lacks transparency in estimating resource usage.
The feature I appreciate the most about SAP IQ is the compression, which is very good; we cannot compare with any other type of EDW.
The most valuable feature of SAP IQ for us is that it works very effectively with the SAP BusinessObjects which we use it with.
We had a comparison with Databricks and Snowflake a few months back, and this auto-scaling takes an edge within Snowflake; that's what our observation reflects.
I have used the Snowflake Zero-Copy Cloning feature in the past while prototyping data in lower environments. This feature is helpful as it saves a lot of time during the data replication process.
Snowflake is a data lake on the cloud where all processing happens in memory, resulting in very fast query responses.
| Product | Market Share (%) |
|---|---|
| Snowflake | 10.4% |
| SAP IQ | 2.4% |
| Other | 87.2% |

| Company Size | Count |
|---|---|
| Small Business | 6 |
| Midsize Enterprise | 2 |
| Large Enterprise | 16 |
| Company Size | Count |
|---|---|
| Small Business | 29 |
| Midsize Enterprise | 20 |
| Large Enterprise | 57 |
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 provides a modern data warehousing solution with features designed for seamless integration, scalability, and consumption-based pricing. It handles large datasets efficiently, making it a market leader for businesses migrating to the cloud.
Snowflake offers a flexible architecture that separates storage and compute resources, supporting efficient ETL jobs. Known for scalability and ease of use, it features built-in time zone conversion and robust data sharing capabilities. Its enhanced security, performance, and ability to handle semi-structured data are notable. Users suggest improvements in UI, pricing, on-premises integration, and data science functions, while calling for better transaction performance and machine learning capabilities. Users benefit from effective SQL querying, real-time analytics, and sharing options, supporting comprehensive data analysis with tools like Tableau and Power BI.
What are Snowflake's Key Features?
What Benefits Should You Look for?
In industries like finance, healthcare, and retail, Snowflake's flexible data warehousing and analytics capabilities facilitate cloud migration, streamline data storage, and allow organizations to consolidate data from multiple sources for advanced insights and AI-driven strategies. Its integration with analytics tools supports comprehensive data analysis and reporting tasks.
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