A curated list to help you manage temporal data across many modalities 🚀.

An open-source, opinionated time-series database built on PostgreSQL & ClickHouse.

A comprehensive addon tool for managing data grid environments by distributed workspaces and online use case bundles

Python SDK for LUSID by FINBOURNE, a bi-temporal investment management data platform with portfolio accounting capabilities.

A lightweight Pythonic data model for time series data, interoperable with NumPy, Pandas and Polars.

Hyperlocal disaster damage assessment using bi-temporal street-view imagery and pre-trained vision models https://doi.org/10.1016/j.compenvurbsys.2025.102335

Java SDK for LUSID by FINBOURNE, a bi-temporal investment management data platform with portfolio accounting capabilities.

Perfect memory. Exact reasoning. Complete history for AI agents.

A cognitive substrate for AI agents — hyperdimensional memory with first-class goals, beliefs, sensory, self-model, and a non-destructive unlearn primitive. Rust top to bottom, embedded-first, no LLM in the read path. One binary, no query language.

An experimental distributed database built in Rust. It uniquely combines Vector Similarity Search (for AI applications) with Bi-Temporal Data Management (Time Travel) and Distributed Consensus (Raft).

A benchmark for long-horizon organizational memory in AI agents: a synthetic, bi-temporal, multi-author/multi-channel corpus with a evaluation harness over publicly available memory systems.

Bi-temporal append-only DB server

Temporal tables extension for PostgreSQL. Automatically tracks Transaction Time (system time) on any table using range types and a high-performance C-based AFTER ROW trigger.

XTDB bi-temporal player state store for football analytics

JavaScript SDK for LUSID by FINBOURNE, a bi-temporal investment management data platform with portfolio accounting capabilities.

Local MCP memory server for LLMs. Bi-temporal graph + vector + Cypher queries + auto-write/auto-recall hooks for Claude Code. Works with Ollama, LM Studio, Anthropic, OpenAI.

engramx's bi-temporal mistakes + structural code-graph as auto-discoverable Claude Code Skills. Catches recurring mistakes before agents repeat them. Apache 2.0, local SQLite, zero cloud.

FloodSense is a deep learning framework for flood detection using bi-temporal Sentinel-1 SAR imagery. It compares pre-event and post-event satellite images to identify flooded areas, supporting multiple datasets (Sen1Floods11, S1GFloods, OmbriaS1)

Financial lakehouse on Apache Iceberg and Databricks: 190K+ SEC filings, bi-temporal modeling, query performance work (clustering + partition pruning), dbt tests, Chroma/Pinecone RAG.