Snowflake and Amazon Redshift compete in the cloud data warehousing category. Snowflake appears to have the upper hand due to its exceptional scalability and flexibility, although Redshift is favored for its strong AWS integration and security features.
Features: Snowflake offers excellent scalability and performance due to its architecture supporting rapid scaling and versatile data processing. It includes features like Snowpipe for seamless data ingestion and Zero Copy Clone for quick environment creation. Redshift, with support for Python user-defined functions and deep AWS integration, excels in security with VPC configuration and offers fast read access optimized for large datasets.
Room for Improvement: Snowflake could enhance geo-spatial queries, improve its user interface, and automate Snowpipe ingestion while offering better support and pricing transparency. Redshift users seek better tools for large dataset snapshots, enhanced query optimization, and improved flexibility for unstructured data management, alongside better performance and integration capabilities.
Ease of Deployment and Customer Service: Snowflake performs well across diverse environments and provides responsive support, though SLA enforcement and communication across time zones can improve. Redshift similarly gains positive feedback on multiple cloud architectures, but support response times can be slower due to fewer personnel.
Pricing and ROI: Snowflake offers a flexible pay-per-use model aligning usage with billing, which users find justifies its higher pricing despite some cost estimation challenges. Redshift is praised for competitive, clear pricing structures, beneficial for long-term deployments, though costs can rise with scaling, affecting ROI as operations expand.
We earned back our investment in Amazon Redshift within the first year.
Whenever we need support, if there is an issue accessing stored data due to regional data center problems, the Amazon team is very helpful and provides optimal solutions quickly.
Documentation that allows anyone with prior knowledge of Redshift or SQL to resolve technical issues.
It's costly when you enable support.
We sought this documentation multiple times but faced difficulty in obtaining it.
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 scalability part needs improvement as the sizing requires trial and error.
We have successfully increased our storage space, which was a smooth process without server crashes before or after scaling.
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.
Amazon Redshift is a stable product, and I would rate it nine or ten out of ten for stability.
Snowflake is highly stable and performs well even with large data sets exceeding terabytes, maintaining stability throughout.
Snowflake is very stable, especially when used with AWS.
Snowflake as a SaaS offering means that maintenance isn't an issue for me.
They should bring the entire ETL data management process into Amazon Redshift.
Integration with AI could be a good improvement.
Integration with AI features could elevate its capabilities and popularity.
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.
The cost of technical support is high.
It's a pretty good price and reasonable for the product quality.
The pricing of Amazon Redshift is expensive.
When it comes to cloud support, the setup cost is very cheap compared to other platforms, such as Oracle or PostgreSQL, which typically require higher costs.
Snowflake's pricing is on the higher side.
Snowflake lacks transparency in estimating resource usage.
Amazon Redshift's performance optimization and scalability are quite helpful, providing functionalities such as scaling up and down.
Scalability is also a strong point; I can scale it however I want without any limitations.
The specific features of Amazon Redshift that are beneficial for handling large data sets include fast retrieval due to cloud services and scalability, which allows us to retrieve data quickly.
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 has contributed to significant cost savings.
| Product | Mindshare (%) |
|---|---|
| Snowflake | 15.1% |
| Amazon Redshift | 7.0% |
| Other | 77.9% |
| Company Size | Count |
|---|---|
| Small Business | 27 |
| Midsize Enterprise | 21 |
| Large Enterprise | 29 |
| Company Size | Count |
|---|---|
| Small Business | 30 |
| Midsize Enterprise | 20 |
| Large Enterprise | 61 |
Amazon Redshift is a dynamic data warehousing and analytics platform offering scalability and seamless AWS integration for high-performance query processing and diverse data management.
Amazon Redshift provides robust data integration capabilities with AWS services like S3 and QuickSight, enabling efficient data warehousing and analytics. It is known for fast query performance due to its columnar storage and can handle diverse file formats. With a user-friendly SQL interface, Redshift supports data compression and offers a strong cost-performance ratio. Its secure VPC configurations and compatibility with data science tools enhance its functionality, although there is room for improving snapshot restoration, dynamic scaling, and processing large datasets.
What are the key features of Amazon Redshift?In industries, Amazon Redshift is essential for managing extensive datasets for business intelligence, operational insights, and reporting. It supports data integration from ERPs and S3, handles SQL queries for comprehensive analysis, and facilitates data storage and transformation. Companies use it for predictive modeling and connect with BI tools like Tableau and Power BI to derive actionable insights.
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.
We monitor all Cloud Data Warehouse 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.
