Three SQL Keywords for Finding Missing Data

QuestDB is an open-source time-series database designed for high-performance workloads, offering ultra-low latency and high ingestion throughput. It supports SQL and Parquet, ensuring data portability and AI readiness without vendor lock-in. The database is particularly suitable for applications requiring real-time data processing, such as public transport systems and industrial machinery sensors, where data continuity is crucial for safety and reliability. QuestDB enhances standard SQL functionalities with extensions like SAMPLE BY, FILL, and ALIGN TO CALENDAR to facilitate the identification and handling of missing data in time-series datasets. These extensions simplify the process of finding gaps in data, allowing users to perform time-series interpolation efficiently without complex queries. The article demonstrates this capability using a trades dataset of Bitcoin and Ethereum transactions, highlighting the ease with which QuestDB can manage missing data, a task that often proves cumbersome in traditional relational databases.

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