Amazon EMR and Snowflake are major competitors in the data processing solutions category. Snowflake appears to have the upper hand in terms of efficiency and scalability, while Amazon EMR is favored for cost-effectiveness.
Features: Amazon EMR offers auto-scaling and robust integration capabilities, efficiently managing big data tasks with minimal maintenance needs. Snowflake provides flexible scalability, supports multiple data formats, and includes advanced features like zero-copy clone, simplifying data management and enhancing data sharing capabilities.
Room for Improvement: Amazon EMR could benefit from improved web support, increased ease of use for beginners, and better version update management. Snowflake needs clearer pricing models and stronger integration with machine learning functions as well as enhancements in governance, reporting, and ETL capabilities.
Ease of Deployment and Customer Service: Amazon EMR excels in public cloud deployment and generally positive customer service ratings, despite some inconsistencies. Snowflake offers deployment flexibility across public and private cloud options, though it receives mixed feedback on technical support consistency.
Pricing and ROI: Amazon EMR is cost-effective when EC2 fees are well-managed, though unmanaged costs can rise substantially. Snowflake's pricing is generally perceived as higher but transparent and flexible with a pay-as-you-go model, offering value proportional to its features. Both platforms report high ROI, particularly for enterprises transitioning from on-premise systems.
We get all call support, screen sharing support, and immediate support, so there are no problems.
They help with billing, cost determination, IAM properties, security compliance, and deployment and migration activities.
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.
Scalability can be provisioned using the auto-scaling feature, EC2 instances, on-demand instances, and storage locations like block storage, S3, or file storage.
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.
Regular updates, patch installations, monitoring, logging, alerting, and disaster recovery activities are crucial for maintaining stability.
Snowflake is very stable, especially when used with AWS.
Snowflake as a SaaS offering means that maintenance isn't an issue for me.
The cost factor differs significantly. When you run Spark application on EKS, you run at the pod level, so you can control the compute cost. But in Amazon EMR, when you have to run one application, you have to launch the entire EC2.
There is room for improvement with respect to retries, handling the volume of data on S3 buckets, cluster provisioning, scaling, termination, security, and integration between services like S3, Glue, Lake Formation, and DynamoDB.
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.
Costs are involved based on cluster resources, data volumes, EC2 instances, instance sizes, Kubernetes, Docker services, storage, and data transfers.
Snowflake's pricing is on the higher side.
Snowflake lacks transparency in estimating resource usage.
Amazon EMR helps in scalability, real-time and batch processing of data, handling efficient data sources, and managing data lakes, data stores, and data marts on file systems and in S3 buckets.
The compute demand has decreased and it has reduced the cost significantly.
Snowflake is a data lake on the cloud where all processing happens in memory, resulting in very fast query responses.
Being able to perform AI and Machine Learning in the same location as the data is quite advantageous.
| Product | Market Share (%) |
|---|---|
| Snowflake | 17.7% |
| Amazon EMR | 3.3% |
| Other | 79.0% |
| Company Size | Count |
|---|---|
| Small Business | 6 |
| Midsize Enterprise | 5 |
| Large Enterprise | 11 |
| Company Size | Count |
|---|---|
| Small Business | 28 |
| Midsize Enterprise | 20 |
| Large Enterprise | 57 |
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?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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