I don't see a link to the notebook

Very cool. Thanks. Nice summary.

it there a possibility that there is an error in the docker image after doing everything exactly as shown i can find the installed extensions only extension i can list using \dx command is plpgsql | 1.0 | pg_catalog | PL/pgSQL procedural language

lovely like usual , there is indeed allot to learn but were getting closer :) Bless you, ps. Regarding storing structured and unstructured data in the same table : are you using the technique to store complete structured tables inside a JSONB ? We thought about this approach but dropped it in favor of separating structured from unstructured data to prevent mis-matching and allow for better isolation/scaling. Still experimenting but currently our set-up creates 1 table per structured document and infer the SCHEMA dynamically on upload + the embedding. Than the Agent decides on run-time which tables to query on. Unstructured documents can be bundled together more easily but placing all document types together can give false-positive search results ?

Thank you, clear and straightforward.

Quite useful tutorial! Thanks for bringing it. A few questions that come to my mind: 1- How could I get rid of proprietary image in docker? I bet it is possible to get our existing PG instance and just drop in the necessary extensions and should work as well, but just want to confirm. 2- It looks easy to delegate to the PG extension to communicate with ollama and get the embedings, however I see to many roundrtrips in that approach. For a programmatic system that would have to do tens of thousands runs a day, how this perform? Is there a more "straight" way to pull embeddings from ollama and query PG?

great , looking forward learning how to utilize Timescale DB for our AI start-up !

Nice tutorial!

You're not missing out much if you skip the first 15mins and jump to 15:00 right away

When I try to create hypertable, getting ""column type "timestamp without time zone" used for "Column" does not follow best practices,"" Error. The mentioned column is Tiimestamp

Amazing video, learnt a lot. Will make time to read timescale blog regularly.

You should do more tutorials like these

Appreciate the video. Just FYI, you're pronouncing the word "build" like "bulled" throughout the video, but most native speakers pronounce it like "billed"

What's difference between pgvector and pgai

What other Metrics are available for Datadog? I already have CPU, Memory, and Disk available from doing a Postgres integration.

Wonderful video

Really enjoyed the presentation!! I was trying to understand how vacuum cleans up the indexes - would really love an explanation on the same.

pleasantly surprised as I'm a fan of Lance his teachings. We are considering Timescale for our RAG solution(s).

waste of time, DuckDB is x3 times faster.

Incrível, muito obrigado!!

7:40 time bucket function

I thought of making a question, but the autor hasn't answer anyone in that comments below! It's not worth to subscribe!

Always enjoy lessons from industries leader and tech providers !

After importing and applying, it gives me following error After the apply operation, the provider still indicated an unknown value for timescale_service.service.password. │ All values must be known after apply, so this is always a bug in the provider and should be reported in the │ provider's own repository. Terraform will still save the other known object values in the state

Excellent video very bubbly personality. The Terminal sounded really snazzy 😂

Very nice video . I found out about timescale db from one of the KZbin influencers and having the ability to run it locally is a big plus. I was a bit afraid of running docker containers but this helps a lot

top material team, despite the lack of views, this is gold.

What a fantastic conversation! Michael and Stephan's insights highlight PostgreSQL's incredible versatility and its potential to replace specialized tools like Elasticsearch. The deep dive into vector search and PostgreSQL's unique features was particularly enlightening. It's great to see industry leaders advocating for such a powerful and flexible database solution. Can't wait to explore more on how PostgreSQL can streamline and enhance our tech stacks! 🐘🔥

Loved to have talked to you, using Timescale in all of my projects.

dont waste your time.

Baby data scientist here, this is so informative! thanks!

I couldn't get the gem to work with scenic gem, is there a special configuration to be done? i thought using create_view and passing the params should work, because that method should be overloaded by the extension but tit didn't work for me :( any idea?

routing table to new cidr created to AWS console but not propagated to EC2 instance.

how we can do if we have a categorical variable like a region , a town , etc?

How to join the slack ? Link doesnt work and says i need an invite

Hi Sir, Can you suggest me the best approach that suits to build a RAG app for multiple 10K Reports?

This is a MUST watch video for everyone, even skilled ones, as it's like an prime vision of the AS IS of RAG but with a glimpse of the TO BE.

Hi, nice video on advancing RAG to a new level. I'm curious about SQLconnectors, how does this work under the hood? Do you only retrieve the schema of the table or does it share similiar functionality to SQLAgent from langchain?

This video has wrong info, no? Timescale throws errors if both the end_offset and start_offset arent at least twice the bucket width. In examples given in this video, the end_offset is much smaller than the bucket width. Is this something that has changed over time?

This is great!

any chance to get offset for time_bucket_gapfill ?((

This is a great summary. Thank you!

how you can filter on the symbol column without selecting it (where you use Amazone example) ?

my table has june 1 and 2 data. but when i create a materialized view it generates may 31 itself. CREATE MATERIALIZED VIEW daily_avg_temperature WITH (timescaledb.continuous) AS SELECT time_bucket(INTERVAL '1 day', time_column) AS day, device, AVG(max_temperature) FROM pandas GROUP BY day, device; what is the issue

my table has june 1 and 2 data. but when i created a materialized view with timescale continuous aggregate it generates a value for may 31 itself which not in the table. CREATE MATERIALIZED VIEW daily_avg_temperature WITH (timescaledb.continuous) AS SELECT time_bucket(INTERVAL '1 day', time_column) AS day, device, AVG(max_temperature) FROM pandas GROUP BY day, device; what is the issue

In my case time is present in the "ts" column and the value present in Unix format wants to see last 24 hrs data how we can see

In my case time is present in the "ts" column and the value present in Unix format wants to see last 24 hrs data how we can see

my table has june 1 and 2 data. but when i create a materialized view it includes may 31 also. CREATE MATERIALIZED VIEW daily_avg_temperature WITH (timescaledb.continuous) AS SELECT time_bucket(INTERVAL '1 day', time_column) AS day, device, AVG(max_temperature) FROM pandas GROUP BY day, device; what is the issue

How would you make continuous aggregate if data is stored in jsonb and differs from sensor to sensor? Imagine I have one sensor with temperature and humidity and another one with wind speed & wind direction. All the data is kept in a flexible struct fashion as jsonb. Is it possible to create 1 hour continuous aggregate with avg, min & max out of this data? Thanks!

In other dataflow libraries the intervals require a time anchor reference point. For example you would clarify that 5 min intervals begin at 00:00pm, 00:05pm, 00:10pm etc and not 00:01pm, 00:06pm, 00:11pm. How does Timescale do this? Is it defaulted to midnight UTC?