spring-data-jpa-temporal VS xtdb

Can I ask something? I recently started working on a library (this) using Java 16 but I had hoped on supporting minimum Java 8 (since it's a Spring extension and Spring supports Java 8).

You don't necessarily need to embed it into the programming language itself to get a ton of value. XTDB (https://github.com/xtdb/xtdb) offer a Clojure, Java and HTTP API for interacting with the database, which is bitemporal and lets you query the database for a specific point in time for example.

XTDB is a bitemporal and dynamic relational database for SQL and Datalog, written in Clojure. The Python application I work on uses XTDB for its bitemporal and schema-less nature. There were a few Python clients that looked unmaintained and lacked some features we needed, so I tried to build something that would have fit our own requirements in hindsight. This includes:

it's bitemporal, will be SQL-compatible, and also has another query-language - XTQL :

https://github.com/xtdb/xtdb/tree/2.x/dev/xtql

You can also consider other durable Datalog options like datahike or datalevin which can work either as lib (SQLite style) or in a client-server setup; if you want to play with bi-temporality XTDB is a rock solid option with very good support and documentation.

You could look into http://xtdb.com/ if you want an open source alternative

XTDB, or Cross-Time Database, is a distributed and transactional database system designed to handle complex and changing data with ease. It is based on a bitemporal model, which allows for the tracking of both the valid time and transaction time of data, enabling powerful and flexible querying capabilities. With XTDB, developers can work with immutable data structures, which simplifies development and improves reliability. Its graph query language, Datalog, provides a powerful and expressive way to navigate relationships within the data.