Question: I need a unified data management system that combines the benefits of data lakes and data warehouses, do you know of any solutions that fit this description?

For a unified data management system that offers the best of both data lakes and data warehouses, take a look at Databricks. This data engineering platform now has generative AI built in to span data engineering, analytics and governance in one environment. It supports a broad set of tools and integrations, including ETL, data ingestion, business intelligence and AI, all on a lakehouse foundation. That means you get the benefits of both scalability and unification, and it's a good choice for those who want a single system for data management.

Another good choice is Teradata. The Teradata VantageCloud platform offers a single, integrated and harmonized data foundation for an organization, supporting a variety of workloads like lakehouses, data lakes, data warehouses and AI/ML. It can be deployed in public cloud, hybrid cloud or on-premises environments, so it's flexible and scalable. With features like ClearScape Analytics and pay-by-use pricing, Teradata can help accelerate innovation and deliver data-driven insights.

Cloudera has a strong option, too, with its hybrid data platform. Based on the open-source Apache Iceberg project, Cloudera integrates data from multiple sources into a single, trusted system for real-time insights, automated data pipelines and big analytics. It's good for secure data ingestion, processing and analysis in the cloud and on-premises, and it's a good choice for businesses that want to span data silos and get more out of their operations.

If you're already committed to the Postgres database engine, EDB Postgres AI offers a single system for transactional, analytical and AI workloads. It includes native AI vector processing, an analytics lakehouse and hybrid data management, so it's a good foundation for Postgres-based workloads that incorporate AI and analytics. EDB Postgres AI is available with high availability and performance, and it can be deployed in a variety of ways, including cloud-managed services and self-managed software.