CREATE VIEW IF NOT EXISTS world_facts_as_of_now AS
SELECT
rowid, txn_time, valid_time,
e, a, v, ns_user_ref, fact_meta
FROM (
SELECT *,
ROW_NUMBER() OVER (
PARTITION BY e, a
ORDER BY valid_preferred DESC, txn_id DESC
) AS row_num
FROM world_facts
) sub
WHERE row_num = 1
AND assert = 1
ORDER BY rowid ASC;
It would be interesting to see what Turso's (SQLite fork) recent DBSP-based Incremental View Maintenance capability [0] would make of a view like this.
[0] https://github.com/tursodatabase/turso/tree/main/core/increm...
I really need to complete this thing and run some data through it... like, how poor is poor really? Can it be just enough for me to make a getaway with smol SaaS apps?
All of it works quite well and is decently performant. We can ask questions like, how many domains did we own on March 13th, 2024? Or look at the entire lifecycle of a domains ownership (owned, released, re-acquired, transfered, etc).
The big challenge and core issue we discovered though is that our data sucks. QAing this new capability has been a moving target. Tons of mistakes over time that were partially undone or manually undone without proper audit trail. Ghost records. Rapid changes by our bulk editor tool a->b->a->b that need to get squashed into just a->b. The schema of our database has evolved over time, too, which has made this tough to view a consistent representation of things even if the fields storing that data were renamed. When the system was first introduced, we had ~5 columns to track. Now we have over 30.
Suffice to say if I were to do things over again, I would implement a much better change tracking system that bakes in tools to clean/erase/undo/soft-delete/hard-delete mistakes so that future me (now) wouldn't have so many edge cases to deal with in this time traveling system. I'd also like to just make the change tracking capable of time travel itself, versus building that as a bolt-on side table that tracks and works from the change table. Transitioning to an EAV (entity-attr-value) approach is on my spike list, too. Makes it easier to just reduce (key,val) tuples down into an up to date representation versus looking at diffs of before/after.
Really interesting stuff. I learned a lot about this from Clojure/Datomic and think its quite neat that so many Clojurists are interested in and tackling this problem. As the author notes in this post, XTDB is another one.
I feel like "two systems" is the problem.
Writes should either be traditional schema -> standard log of all changes, OR, should be "everything is a log", and the system keeps the "current" view updated, which is just a special case of the "as of" query, where "as of" is always "now".
How badly my schema will behave (in my SQLite-based architecture) is to be discovered. I will hopefully be in a position to run a reasonable benchmark next week.
A follow-up blog post is likely :sweat-smile:
Several are out on YouTube. One with Richard Snodgrass is yet to be published... waiting for that eagerly!
ref. topics and links to videos: https://github.com/orgs/xtdb/discussions/4419
"Decades in the making: Bitemporality in SQL, with Rob Squire"
"As-Of joins and database architecture, with Arjun Narayan (co-founded Materialize)"
"Building an identity service on XTDB, with Andrew Maddock (Foundry OS)"
"Solving FinTech pains with Suresh Nageswaran (Senior Director, Grid Dynamics)"
"A meeting with the one and only Richard T. Snodgrass."
"Building a payments integration system on XTDB, with Edward Hughes"Wait no longer! I just updated the page with the unlisted video link: https://youtu.be/6Q_pAI20QPA
We are hoping to record another (more polished) session with Professor Snodgrass soon :)
100%. This is a regret that I have in our lifecycle tracking. We effectively are updating a giant spreadsheet (table) and tracking side effects of those updates. I would much rather work in a log/event based system kinda flipping that on its head, where we track events like domain_renewed or domain_transferred.
As it stands we track that the renewed_at attribute changed, and have to infer (along with other fields) things like "were you a renewal event?" which has changed meaning over time.
Alas change tracking wasn't even part of the spec of this original feature... so I am glad I had the foresight to institute change tracking from 2022, as imperfect as it is currently.
Hallelujah!!
Straight-up copy-paste from my development notes...
* what pivots in current db vs temporal db?
What is the difference between these pictures?
#+BEGIN_SRC text
("Current" DB)
CRUD records
^
|
v
[ current view ] -- update --> [ facts log ]
---------------------------------------------------------
[ current view ] <-- update -- [ facts log ]
| ^
v |
READ records WRITE records (as facts)
("Temporal" DB)
- Hint: It is /not/ the schema. It is /what/ "pivots".
- In both cases the current view can be understood to be a pivot table of the facts log.
- BUT in the current DB, we must "pivot" the /process/, i.e. take a CRUD op and transform it into an audit log. This /must/ be done synchronously in in real-time. Whereas in the Temporal DB's case, we must "pivot" the stored data, which we can do at any point in query time, as of any point in time of the log.
- The complexity of Current DBs derives from /live process management/ challenges. Whereas the complexity of Temporal DBs derives from /retroactive process management/ challenges.
/now/ is /never/ cheap. It is the most expensive non-fungible thing. Once it's gone, it's gone. Fail to transact an audit trail for the CRUD operation? Too bad. Better luck next time. Whereas disk space is cheap, and practically infinite which affords Temporal DBs greater opportunity to find a better trade-off between essential complexity and DB capabilities. At least as long as disk space remains plentiful and cheap.
This is why if we are modeling a Temporal DB over a Current DB, it is preferable to write all tables as /fact/ tables and query their auto-generated 'current view' versions, for normal query needs. For audit / analysis needs, we can snapshot the facts tables and operate on those out-of-band (detached from the live app). Impedance mismatch occurs when trying to run /both/ current CRUD tables (writing to audit logs) for some parts of the schema, in parallel with a "main" facts table for all fact-records. In a given data system, it is better to do either one or the other, not both at the same time.
I just finished building out all of that + more (e.g., data lineage, multi-verse, local overrides, etc), also on PG. Reach out if you want to chat and get nerd sniped!
* Your main table has the correct shape, and the derived log too! * MOST of the queries are to that and for now
https://cloud.google.com/spanner/docs/timestamp-bounds#exact...
If you don't mind sharing, I'm curious why you feel this way.
In a bitemporal database, every regular looking join over the current state of the world is secretly an AsOf join (across two dimensions of time), without constantly having to think about it when writing queries or extending the schema.
As a side project, I'm writing a CLI to tie environment variables to project directories ( https://github.com/bbkane/enventory ) and share env vars between projects with a "reference" system. Similar to direnv but in a central SQLite DB.
See https://github.com/bbkane/enventory/tree/master/dbdoc for how the schema looks, but it's a few tables with foreign keys to each other to support the "reference" system.
Unfortunately those foreign keys mean I don't have a way to "undo" changes easily. So instead I added a confirmation prompt, but I'd still like that undo button.
Hopefully in subsequent blog posts you can follow up on your "Model an example domain of sufficient complexity" TODO and make this a bit less abstract (and hopefully more understandable) to me.
When I write code, it’s as much a cognitive tool as it is a tool to make things happen in the system. It develops thoughts as much as it develops system behavior.
Involving AI changes this quite a bit, but I feel like I’m making my way to a balance where it supports rather than replaces (or worse: disrupts) my cognitive processes.
This isn't as general as your setup, but I think it would work ok with my foreign key issue.
So you have a pet table with an ID, birth date, type, name, whatever, and ‘valid_range’.
That last column is a date_range column. Combined with the ID it serves as a unique key for the table. Records are inserted with a date grange from now() to infinity.
To update a record, you call a stored procedure. It creates the new record with that same date range, and updates the old record to be valid up to (but not including) now(). The SP ensures the process is done correctly.
You can use the same date range in join tables for the same reason.
This makes it possible to see the full state of any record kept like this at any point in time, see when it was created, or last changed. An audit table records who changed it by holding the ID and timestamp of the change. There is no real deletion, you’d do soft deletion by setting a status.
I suspect this wouldn’t work well for very high volume tables without sharping or something. But for CRUD tables that don’t change a lot it’s fantastic.
The only thing that’s not smooth is future updates. If you need a new non-null column, it ends up added to all records. So you can either set a default and just deal with the fact that it’s now set on all old records, leave it as nullable and enforce non-null in code, or enforce it only on insert in a trigger or the SP I described.
I’ve found it much easier to use than some sort of ‘updates’ table storing JSON changes or EAV style updates or whatever.
Programming is writing for me. So, yes I am the same... I need to type (or sometimes write it longhand), to make progress.
I gave LLMs a fair shake, but generative mode usage overwhelms my nervous system. I could use 'em, maybe, for pattern-recognition. But using an expressive language (Clojure) means I can eyeball my source code and/or grep through it to maintain a good enough view of my system. This also applies to most third-party code I use from the Clojure ecosystem. Libraries tend to be small (a few thousand lines of code), and I can skim-read through them quick enough.
I know there is a black art to it that one is supposed to learn, in order to get useful results, but so far, the incentive isn't strong enough for me.
So, hand typing / writing it is... might as well feel satisfied using my nice keyboard and little notebook, on my way to obsolescence. No?
This is the minimal "standard record" that one can use, for all facts pertaining to all domain entities in one's system:
system_time, valid_time, Entity, Attribute, Value, assert/redact
- For small-middle-heavy usage (anything that (reasonably) fits on one machine) how to use existing database technology, so that one can store and query this stuff sufficiently fast. This is what I'm trying to do with SQLite... partly because the "V" of E/A/V benefits from SQLite's "Flexible Typing" system. In SQLite parlance, E, A are TEXT, and V is NUMERIC.
- For at-scale usage (anything that needs many machines), how to make a data system from scratch to store log-structured information efficiently, and how to query it efficiently. See what the Datomic, XTDB, and RedPlanetLabs/Rama people are doing. Essentially: separate storage and compute, event-source everything, and build a system from scratch to use it efficiently and fast at scale.
For your case, I feel like your best bet would be to create the global order in the first place... i.e. force all writes through a single (and single-threaded) writer process, and fetch reads off one or more independent reader processes (I'm doing this with WAL-mode SQLite).
But I could be totally wrong --- this is my first foray into the freaky world of temporal data systems :D
I do something like 4000 inserts a second, but maybe only a few queries a minute, so I use an "invalidated_by" column which (eventually) points to the newer record, and I update it on query instead of insert (when the multiple nulls are discovered and relevant)
Clojure doesn't have much manpower, being a niche language and all, so maybe that's where your impression comes from. It's hardly on purpose, and there's many examples of software that ships with another language as public API.
Rama is written in clojure but the main api is java
Klipse is written in cljs but is marketed as a "javascript library"
Even Datomic maintains a java api
Maybe it's time (hehe) someone started a 6NF Conf.
FWIW I think you’re thinking of “memento”
an object or item that serves to remind one of a person, past event, etc.; keepsake; souvenir.Here is the core of it:
CREATE TABLE time_travel_daily (
domain TEXT NOT NULL,
valid_range tstzrange NOT NULL,
valid_from timestamptz GENERATED ALWAYS AS (lower(valid_range)) STORED,
valid_to timestamptz GENERATED ALWAYS AS (upper(valid_range)) STORED,
tld TEXT,
owned BOOLEAN,
acquired_at timestamptz,
released_at timestamptz,
registrar TEXT,
updated_at timestamptz,
accounting_uuid TEXT,
offer_received_date timestamptz,
payment_received_date timestamptz,
sold_at timestamptz,
sold_channel TEXT,
last_renewed_at timestamptz,
expires_at timestamptz,
transfer_started_at timestamptz,
transfer_completed_at timestamptz,
transfer_eligible_at timestamptz,
snapshot_json JSONB NOT NULL,
inserted_at timestamptz DEFAULT NOW() NOT NULL,
source_data_change_id INT,
PRIMARY KEY (domain, valid_range)
);
CREATE INDEX ttd_domain_idx ON time_travel_daily(domain);
CREATE INDEX ttd_gist_valid_range_idx ON time_travel_daily USING gist(valid_range);
CREATE INDEX ttd_owned_valid_range_idx ON time_travel_daily USING gist(valid_range) WHERE owned = TRUE;
CREATE INDEX ttd_registrar_idx ON time_travel_daily(registrar) WHERE registrar IS NOT NULL;
CREATE INDEX ttd_source_data_change_id_idx ON time_travel_daily(source_data_change_id) WHERE source_data_change_id IS NOT NULL;
UPDATE time_travel_daily
SET valid_range = tstzrange(lower(valid_range), target_date::timestamptz, '[)')
WHERE domain IN (
SELECT DISTINCT dc.domain
FROM data_changes dc
WHERE dc.invalidated IS NULL
AND dc.after IS NOT NULL
AND dc.modified_at::date = target_date
)
AND upper(valid_range) IS NULL -- Only close open ranges
AND lower(valid_range) < target_date::timestamptz; -- Don't close ranges that started today SELECT COUNT(DISTINCT domain)
FROM time_travel
WHERE (CURRENT_DATE - INTERVAL '90 days')::timestamptz <@ valid_range
AND owned;
Instead of finding records where the start is less than, end is greater than, you can just say find me rows that will cover this point in time. The GiST index on valid_range does the heavy lifting.
Lots of handy range-specific query tools available: https://www.postgresql.org/docs/17/functions-range.html
And it’s PG’s range queries that make this shine, as you showed. If you had to simulate the range with two columns all the queries would be a pain.
But that’s very smart. Never considered it.
> Git simply refuses to transact the conflict into the live state of the codebase, until someone a) fixes the conflict manually and b) tells git that the conflict is resolved.
This is something that a lot of people seem to forget or maybe never knew, they think that the git cli's merge heuristics are somehow sound and go all YOLO with rewriting history with maybe-correctly merged code (rebase). Sometimes the same people who voice loud objections about LLM coding assistants...
I'm playing with https://github.com/hettie-d/pg_bitemporal right now and it seems great so far.
On thinking more this morning I think I can keep my original tables and add append-only "log" tables with triggers to keep them up to date when the main tables change. That doesn't slow down my main tables performance (they only contain the current data) and also allows me to incrementally change my db (adding new tables + triggers is easier than changing existing ones).
I've made https://github.com/bbkane/enventory/issues/122 to track this idea, though I'm not sure when (or even if) I'll have time to really play with the idea (much less "productionalize" it- add support for all enventory events, tab completion on the CLI, tests, UI, etc...).
But I'm at least tracking it for when I get time and motivation! Thanks for writing the post and replying to my comment.
TIL, thank you :)