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lucidarium-systems
pydbsp
Jupyter Notebook2024–2026
lucidarium-systems / pydbsp

pydbsp

This library provides an implementation of the DBSP language for incremental streaming computations.

Libraries & SDKs
Explore on GitHubRead Hacker News discussions
4Distinct people
9Mentions
0Explicit recommenders
160GitHub stars
REPOSITORY AT A GLANCE

What to know before exploring

What it is

This library provides an implementation of the DBSP language for incremental streaming computations.

GitHub

Where it is used

No documented product use has been verified yet.

What people are saying

No recommendation phrase was found in the indexed comments.

No classified warning is attached to this page. Read the discussions before treating silence as approval.

Also in these discussions

No other repository is repeatedly linked in the same discussions.

This week on Hacker News

Nov 7–Nov 14 UTC · Direct repository links and separately labeled related project stories. Indexed through 11/14/2026, 5:04:57 PM UTC.

No direct repository links were found in the indexed HN discussions over the past seven days. Older discussions are available below.

Mentions over time

HN mentions by month9 dated mentions

Observed mentions: 2024-09-29 17:45:41 UTC to 2026-05-18 01:30:58 UTC.

012342024-09-01 00:00:00 UTC to 2024-10-01 00:00:00 UTC (exclusive): 1 mentions; 0 submissions, 1 commentsSep 20242024-10-01 00:00:00 UTC to 2024-11-01 00:00:00 UTC (exclusive): 4 mentions; 2 submissions, 2 comments2024-11-01 00:00:00 UTC to 2024-12-01 00:00:00 UTC (exclusive): 2 mentions; 1 submissions, 1 comments2024-12-01 00:00:00 UTC to 2025-01-01 00:00:00 UTC (exclusive): 0 mentions; 0 submissions, 0 comments2025-01-01 00:00:00 UTC to 2025-02-01 00:00:00 UTC (exclusive): 0 mentions; 0 submissions, 0 comments2025-02-01 00:00:00 UTC to 2025-03-01 00:00:00 UTC (exclusive): 0 mentions; 0 submissions, 0 comments2025-03-01 00:00:00 UTC to 2025-04-01 00:00:00 UTC (exclusive): 0 mentions; 0 submissions, 0 comments2025-04-01 00:00:00 UTC to 2025-05-01 00:00:00 UTC (exclusive): 0 mentions; 0 submissions, 0 comments2025-05-01 00:00:00 UTC to 2025-06-01 00:00:00 UTC (exclusive): 0 mentions; 0 submissions, 0 comments2025-06-01 00:00:00 UTC to 2025-07-01 00:00:00 UTC (exclusive): 1 mentions; 0 submissions, 1 comments2025-07-01 00:00:00 UTC to 2025-08-01 00:00:00 UTC (exclusive): 0 mentions; 0 submissions, 0 commentsJul 20252025-08-01 00:00:00 UTC to 2025-09-01 00:00:00 UTC (exclusive): 0 mentions; 0 submissions, 0 comments2025-09-01 00:00:00 UTC to 2025-10-01 00:00:00 UTC (exclusive): 0 mentions; 0 submissions, 0 comments2025-10-01 00:00:00 UTC to 2025-11-01 00:00:00 UTC (exclusive): 0 mentions; 0 submissions, 0 comments2025-11-01 00:00:00 UTC to 2025-12-01 00:00:00 UTC (exclusive): 0 mentions; 0 submissions, 0 comments2025-12-01 00:00:00 UTC to 2026-01-01 00:00:00 UTC (exclusive): 0 mentions; 0 submissions, 0 comments2026-01-01 00:00:00 UTC to 2026-02-01 00:00:00 UTC (exclusive): 0 mentions; 0 submissions, 0 comments2026-02-01 00:00:00 UTC to 2026-03-01 00:00:00 UTC (exclusive): 0 mentions; 0 submissions, 0 comments2026-03-01 00:00:00 UTC to 2026-04-01 00:00:00 UTC (exclusive): 0 mentions; 0 submissions, 0 comments2026-04-01 00:00:00 UTC to 2026-05-01 00:00:00 UTC (exclusive): 0 mentions; 0 submissions, 0 comments2026-05-01 00:00:00 UTC to 2026-06-01 00:00:00 UTC (exclusive): 1 mentions; 0 submissions, 1 commentsMay 2026

Counts come from the repository’s dated source evidence. Index cutoff: 2026-11-02 08:16:59 UTC.

View mention counts and date ranges
UTC ranges include their start and exclude their end. Select a period to filter the source evidence.
PeriodStart (UTC)End (exclusive, UTC)MentionsSubmissionsComments
Sep 20242024-09-01 00:00:00 UTC2024-10-01 00:00:00 UTC101
Oct 20242024-10-01 00:00:00 UTC2024-11-01 00:00:00 UTC422
Nov 20242024-11-01 00:00:00 UTC2024-12-01 00:00:00 UTC211
Dec 20242024-12-01 00:00:00 UTC2025-01-01 00:00:00 UTC000
Jan 20252025-01-01 00:00:00 UTC2025-02-01 00:00:00 UTC000
Feb 20252025-02-01 00:00:00 UTC2025-03-01 00:00:00 UTC000
Mar 20252025-03-01 00:00:00 UTC2025-04-01 00:00:00 UTC000
Apr 20252025-04-01 00:00:00 UTC2025-05-01 00:00:00 UTC000
May 20252025-05-01 00:00:00 UTC2025-06-01 00:00:00 UTC000
Jun 20252025-06-01 00:00:00 UTC2025-07-01 00:00:00 UTC101
Jul 20252025-07-01 00:00:00 UTC2025-08-01 00:00:00 UTC000
Aug 20252025-08-01 00:00:00 UTC2025-09-01 00:00:00 UTC000
Sep 20252025-09-01 00:00:00 UTC2025-10-01 00:00:00 UTC000
Oct 20252025-10-01 00:00:00 UTC2025-11-01 00:00:00 UTC000
Nov 20252025-11-01 00:00:00 UTC2025-12-01 00:00:00 UTC000
Dec 20252025-12-01 00:00:00 UTC2026-01-01 00:00:00 UTC000
Jan 20262026-01-01 00:00:00 UTC2026-02-01 00:00:00 UTC000
Feb 20262026-02-01 00:00:00 UTC2026-03-01 00:00:00 UTC000
Mar 20262026-03-01 00:00:00 UTC2026-04-01 00:00:00 UTC000
Apr 20262026-04-01 00:00:00 UTC2026-05-01 00:00:00 UTC000
May 20262026-05-01 00:00:00 UTC2026-06-01 00:00:00 UTC101

What Hacker News says

9 sources
gobdovan·May 18, 2026
General programming [0], static analysis [1], RDF triple stores [2], authorization systems [3], incremental computation [4] [5], graph DBs [6]. But it is kind of hard to define Datalog exactly, since it is an entire family of technologies based on logic, each extending a clean mathematical model differently. [0] https://github.com/flix/flix [1] https://github.com/rust-lang/polonius [2] RDFox [3] https://github.com/eclipse-biscuit/biscuit [4] https://github.com/vmware-archive/differential-datalog [5] https://github.com/brurucy/pydbsp [6] https://github.com/cozodb/cozo
In Prolog Coding Horror
rebanevapustus·Jun 15, 2025
They did, and their product is great. It is the only database/query engine that allows you to use the same SQL for both batch and streaming (with UDFs). I have made an accessible version of a subset of Differential Dataflow (DBSP) in Python right here: https://github.com/brurucy/pydbsp DBSP is so expressive that I have implemented a fully incremental dynamic datalog engine as a DBSP program. Think of SQL/Datalog where the query can change in runtime, and the changes themselves (program diffs) are incrementally computed: https://github.com/brurucy/pydbsp/blob/master/notebooks/data...
In Datalog in Rust
rebanevapustus·Oct 13, 2024
Datalog does not use backtracking, and is getting ever increasingly more popular. See: - The fastest non-incremental embedded Datalog engine https://github.com/s-arash/ascent - The state-of-the-art non-embedded and non-incremental Datalog engine https://github.com/knowsys/nemo - A python library that contains an embedded incremental Datalog engine https://github.com/brurucy/pydbsp - A Rust library that provides a embedded incremental Datalog engine over property graphs https://github.com/brurucy/materialized-view
In Can logic programming be liberated from predicates and backtracking? [pdf]

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