Datencursors

Datencursors are a data navigation primitive designed for working with time-stamped records. They provide an abstraction for iterating, seeking, and slicing data along a date or date-time axis. In time-series databases, log stores, and financial datasets, a datencursor points to a specific record or interval and exposes operations to move to a given date, advance to the next timestamp, or iterate over a date range. A datencursor maintains alignment with the underlying date index and can accommodate time zones, missing dates, and resampling rules.

Core capabilities typically include seek(date) to position the cursor at or near a target date, next() and prev() to move one step, and range(start, end) to extract records within a period. Some implementations support stepping by fixed intervals (days, hours) or by calendar boundaries (month end, quarter). The abstraction is designed to work whether the data is stored in a database, streamed, or loaded into memory, and it often relies on an indexed date column or compatible time key.

Use cases for datencursors include data analysis workflows, real-time dashboards, backtesting in finance, and event-based aggregations in sensor and log data. They help ensure deterministic traversal and can simplify handling of irregular time series where dates may be missing or out of order.

Etymology and status: the term datencursor is a neologism formed from elements meaning data and cursor. It is not a universally standardized term, but appears in some vendor documentation and academic discussions as a conceptual tool for temporal data navigation.

See also: cursor, time-series database, temporal database, date index.