If you want a cloud-based foundation to span your data environment, perform complex analysis and run custom applications in a secure, scalable way, Cloudera is a strong contender. The company's hybrid data platform securely ingests, processes and analyzes data in the cloud and on-premises environments. With a range of data services -- ingest, prepare, analyze, predict and publish -- it can provide real-time insights, automated data pipelines and large-scale application deployment. And with an Apache Iceberg foundation, it's designed to keep data reliable and flexible.
Another powerful option is Teradata, which offers a cloud analytics and data platform that integrates and harmonizes data across an enterprise. Its core product, ClearScape Analytics, provides faster answers and a clear view of your data. The platform can support multiple workloads and can be deployed in public cloud, hybrid cloud or on-premises environments. Teradata supports AI/ML, lakehouses, data lakes, data warehouses and more, so it's a flexible option for optimizing resources and making data-driven decisions.
For those who want a cloud-based foundation for collaboration and data-driven application development, Snowflake is a good option. Snowflake combines data, applications and AI capabilities into a single cloud-based system to improve productivity and enable data-driven decision-making. It supports a broad range of workloads, so it can accommodate different business needs and increase data usage and insights.
Last, IBM Cloud is a broad enterprise cloud platform geared for highly regulated industries. It offers a secure, resilient and high-performance foundation for applications with AI and machine learning abilities. Key features include security and compliance, easy scaling for AI workloads, and a broad range of products and solutions geared for industries like financial services and healthcare.