Wide events represent a significant advancement in how data is logged and processed for observability. Unlike traditional logging mechanisms that may only capture limited information, wide events include a vast number of fields, which can number from tens to hundreds. This allows extensive slicing and dicing of data for analyses but introduces challenges in typical relational database storage, which struggles to adapt to data that is inherently flexible. Traditional databases are inefficient for processing queries that aggregate data from only a subset of available fields, as all fields must still be read. In contrast, column-oriented analytical databases like ClickHouse are better suited for this type of storage but still require predefined schemas, thereby limiting their flexibility. The emerging solution, VictoriaLogs, is an open-source database developed specifically for wide events, allowing schemaless ingestion of data while ensuring efficient storage and query performance. This innovative approach represents a growing trend towards flexible data architectures, especially important for observability in software systems.