4/4/2023 0 Comments Lakehouse by alta![]() ![]() However, this approach comes with several drawbacks, including the higher costs due to maintenance and vendor lock-in, necessitating the need for more cost-effective data management approaches. It prioritizes certain factors, such as the integrity of the provided data. This data warehouse process has its advantages. ![]() This data gets processed into a different database format that’s optimized for BI (business intelligence) use cases, where it’s more effective for complex queries. Usually, data warehouses pull data from databases, which have a specific structure known as schema. Defining data warehousesĪ data warehouse collects data from various data sources within an organization to extract information for analysis and reporting. To understand how a data lakehouse works, let’s first take a brief look at data warehouses and data lakes. What is a data lakehouse?Ī data lakehouse shores up the gaps left by data warehouses and data lakes - two commonly used data architectures. It lets them reach a middle ground where they can get the best of both worlds in terms of data storage and data management. This is where a data lakehouse has emerged as a major problem-solver in the last few years.Ī data lakehouse can help organizations move past the limitations of data warehouses and data lakes. That’s why data architects envision a single system to store and use data for varying workloads. Despite their pros, each also has its limitations. ![]() Both data warehouses and data lakes have been serving companies well for a long time. ![]()
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