Find out in this report how the two Cloud Data Warehouse solutions compare in terms of features, pricing, service and support, easy of deployment, and ROI.
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.
Scalability can be provisioned using the auto-scaling feature, EC2 instances, on-demand instances, and storage locations like block storage, S3, or file storage.
Most of our functions or jobs are queued due to that.
Regular updates, patch installations, monitoring, logging, alerting, and disaster recovery activities are crucial for maintaining stability.
I have faced stability issues, mainly due to the storage my organization has, though I am not sure if it's specifically due to the tool.
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.
Costs are involved based on cluster resources, data volumes, EC2 instances, instance sizes, Kubernetes, Docker services, storage, and data transfers.
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.
Amazon EMR provides out-of-the-box functionality because we can deploy and get Spark functionality over Hadoop.
The product is not complex; I do not have to create stored procedures, functions, or views.
| Company Size | Count |
|---|---|
| Small Business | 6 |
| Midsize Enterprise | 5 |
| Large Enterprise | 11 |
| Company Size | Count |
|---|---|
| Small Business | 30 |
| Midsize Enterprise | 10 |
| Large Enterprise | 48 |
VMware Tanzu is a robust platform tailored for data warehousing, complex analytics, BI applications, and predictive analytics. It excels in scalability, performance, and parallel processing, enhancing data handling efficiency. Users report significant productivity improvements and streamlined operations, making it ideal for comprehensive data solutions.
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.
