Order Book Imbalance Analysis with QuestDB Arrays

QuestDB is an open-source time-series database designed for high-performance workloads, such as trading floors and mission control, offering ultra-low latency and high ingestion throughput with a multi-tier storage engine. It supports Parquet and SQL, ensuring data portability and is geared for AI applications without vendor lock-in. The analysis of order book imbalance (OBI) is simplified with QuestDB's 9.0 release, which introduces N-dimensional array types to efficiently store and analyze order book data using NumPy-like arrays. This replaces the traditional need for multiple columns to store data at various price levels, allowing for more streamlined data representation and analysis with built-in array functions. In a tutorial using synthetic Bitcoin data, the setup of QuestDB with Grafana via Docker Compose is demonstrated for exploring market states, analyzing OBI under different scenarios, and visualizing data through heatmaps and timeseries charts. The tutorial highlights how QuestDB's capabilities facilitate complex order-book-imbalance analysis and visualization without the need for external tools, encouraging users to apply these methods to real-world data from sources like Coinbase or Binance.