TIMPid

TIMPid is an open-source software framework for time-series data processing and indexing in distributed computing environments. It provides ingestion pipelines, an indexed storage layer, and a streaming compute engine to support both real-time and historical queries on time-ordered data.

The architecture centers on a core runtime with pluggable backends for storage and computation. TIMPid uses time-based partitioning and segment-oriented storage to enable scalable ingestion and efficient querying. The data model centers on records that include a timestamp, a value, and optional metadata tags; the system supports basic schema discovery and a registry to handle semi-structured inputs. The framework emphasizes modularity, allowing users to interchange storage backends, processing engines, and query interfaces.

Key features include batch and streaming processing, windowed aggregations, downsampling, retention policies, and fault-tolerant execution through idempotent operators. It provides backpressure-aware processing, multi-tenant isolation, and connectors to common data sources and sinks. Query interfaces typically offer REST or gRPC endpoints, along with a programmatic API for embedded usage. TIMPid also supports basic data quality controls, such as schema validation and anomaly detection hooks, to assist in maintaining data integrity across pipelines.

Use of TIMPid spans several domains, including Internet of Things sensor networks, infrastructure monitoring, financial tick data analytics, and scientific experiments requiring fast time-series queries and robust long-term storage. TIMPid originated as a research project in the late 2010s, with its first public release in the early 2020s. It is maintained by the TIMPid Consortium and released under a permissive open-source license. Related topics include time-series databases, stream processing, and data engineering.