VMware Tanzu Data Solutions and Amazon Aurora are competing in the cloud database space. Based on feedback, Amazon Aurora seems to have the upper hand, often perceived as the more robust option due to its features.
Features: VMware Tanzu Data Solutions offers an MPP architecture with capable processing speed and scalability. It supports ETL capabilities and various programming languages, with robust parallel processing and data distribution. Amazon Aurora excels in seamless AWS integration, high availability, continuous backups, and efficient performance, with built-in security and multiple read replicas.
Room for Improvement: VMware Tanzu Data Solutions could improve its scalability, stability, and backward compatibility, alongside better memory handling and latency management. Users express concerns about seamless upgrades and performance consistency. Amazon Aurora, while cost-efficient, needs enhancements in pricing, cryptography, and scaling capabilities, with some users seeking broader integration options and a more competitive cost structure.
Ease of Deployment and Customer Service: VMware Tanzu Data Solutions can be deployed on-premises, hybrid, and private clouds, offering versatility but potentially requiring more technical support. Amazon Aurora focuses on public cloud for simplified deployment. VMware Tanzu is praised for excellent tech support, whereas Amazon Aurora benefits from a larger AWS ecosystem.
Pricing and ROI: VMware Tanzu Data Solutions leverages an open-source model for cost-effective solutions, appealing from a pricing perspective, with optional paid support. Amazon Aurora, acknowledged for performance against cost, is seen as relatively expensive, possibly deterring budget-conscious clients. However, its managed service model adds value, justifying the investment by streamlining operations without managing on-prem infrastructure.
Using Amazon Aurora has saved us significantly in terms of manpower costs, with nearly fifty percent savings compared to an on-premises solution.
Technical support from Amazon is rated very highly.
Most of our functions or jobs are queued due to that.
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.
There are technical challenges, such as the inability to provision the database using a PostgreSQL snapshot directly.
The pricing is reasonable and not overly expensive.
Amazon Aurora offers a 99.9% SLA compared to PostgreSQL. This ensures a high level of availability for our applications.
The product is not complex; I do not have to create stored procedures, functions, or views.
Amazon Aurora is a MySQL and PostgreSQL-compatible relational database built for the cloud, that combines the performance and availability of traditional enterprise databases with the simplicity and cost-effectiveness of open source databases.
Amazon Aurora is up to five times faster than standard MySQL databases and three times faster than standard PostgreSQL databases. It provides the security, availability, and reliability of commercial databases at 1/10th the cost. Amazon Aurora is fully managed by Amazon Relational Database Service (RDS), which automates time-consuming administration tasks like hardware provisioning, database setup, patching, and backups.
Amazon Aurora features a distributed, fault-tolerant, self-healing storage system that auto-scales up to 64TB per database instance. It delivers high performance and availability with up to 15 low-latency read replicas, point-in-time recovery, continuous backup to Amazon S3, and replication across three Availability Zones (AZs).
Visit the Amazon RDS Management Console to create your first Aurora database instance and start migrating your MySQL and PostgreSQL databases.
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.
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