Hope springs eternal in the database business. While we're still hearing about data warehouses (fast analysis databases, typically featuring in-memory columnar storage) and tools that improve the ETL step (extract, transform, and load), we're also hearing about improvements in data lakes (which store data in its native format) and data federation (on-demand data integration of heterogeneous data stores). Presto keeps coming up as a fast way to perform SQL queries on big data that resides in data lake files. Presto is an open source distributed SQL query engine for running interactive analytic queries against data sources of all sizes. Presto allows querying data where it lives, including Hive, Cassandra, relational databases, and proprietary data stores.

Most enterprises are undertaking a digital transformation initiative. Data and analytics modernization is an integral part of this journey. On-premise legacy systems like Hadoop clusters and data warehouses limit innovation and growth due to their old architectures. New cloud-based platforms are becoming an inevitable consideration for many such enterprises. However, they are seeking to reduce the risk and complexity of manual migration from their conventional ETL tools and data lakes to a modern, future state.