Slotar

Slotar is a hypothetical data-management architecture designed to organize time-series data by fixed-duration units called slots. Each slot covers a contiguous time interval, and records with timestamps within that interval are stored together. The approach aims to provide predictable storage usage and fast queries that are bounded by time ranges.

The architecture centers on a slot-centric pipeline. A slot manager allocates and tracks the lifecycle of slots, a slot store persists records, and a slot index maps timestamps to their corresponding slots. Ingestion streams data into the current active slot, often through a write-ahead buffer, while reads resolve a requested time range to one or more slots. Storage backends can be local filesystems or cloud object stores, and slot-level retention policies control data aging and deletion. The design supports versioning and multi-tenancy via slot namespaces and access controls.

Key features include deterministic query performance for time-bounded ranges, per-slot compaction and archival, and modular storage backends. Slotar is intended to integrate with common ingestion and query interfaces, offering compatibility with typical time-series formats and streaming APIs. The slot-based model also aids in data governance by enabling per-slot retention policies and auditing at the interval level.

History and status: Slotar has appeared mainly in academic discussions and experimental prototypes concerning time-series storage and telemetry systems in the 2020s. It is not a widely adopted standard, and practical deployments have highlighted considerations such as the choice of slot granularity, potential fragmentation, and the complexity of cross-slot queries.

See also: time-series databases, log-structured storage, partitioned storage, slot-based indexing, time-based data retention.