Try Rill for free: curl https://rill.sh | sh
Want to take it even further? You can render HTML too! Plus, we're making the backend endpoint public so you can easily build your own programs and workflows that need access to templated data.
Want to take it even further? You can render HTML too! Plus, we're making the backend endpoint public so you can easily build your own programs and workflows that need access to templated data.
www.rilldata.com/blog/rill-in...
www.rilldata.com/blog/rill-in...
In the updated episode, we discussed:
→ Why they worked in secret for a year
→ Why 99% of analytics workloads don't need distributed systems
datatalks.rilldata.com
In the updated episode, we discussed:
→ Why they worked in secret for a year
→ Why 99% of analytics workloads don't need distributed systems
datatalks.rilldata.com
www.youtube.com/watch?v=ejOK...
www.youtube.com/watch?v=ejOK...
Using Gemini's CLI and the Model Context Protocol (MCP), you can explore metrics, identify trends, and generate insights without writing queries manually.
Using Gemini's CLI and the Model Context Protocol (MCP), you can explore metrics, identify trends, and generate insights without writing queries manually.
6 years later: 1M+ monthly users, 10x faster than Spark on the same hardware.
We updated our DTTR episodes. Watch the full talk with @hannes.muehleisen.org
datatalks.rilldata.com
6 years later: 1M+ monthly users, 10x faster than Spark on the same hardware.
We updated our DTTR episodes. Watch the full talk with @hannes.muehleisen.org
datatalks.rilldata.com
👉Subscribe for more conversations with the builders shaping the future of data.
datatalks.rilldata.com
👉Subscribe for more conversations with the builders shaping the future of data.
datatalks.rilldata.com
This video covers:
- Examples for real-time data by day or hour
- Types of time range
- Time grains
- Time zones
www.youtube.com/watch?v=PDFp...
This video covers:
- Examples for real-time data by day or hour
- Types of time range
- Time grains
- Time zones
www.youtube.com/watch?v=PDFp...
"Data engineering is critical because we have the opportunity to have the one human data team."
ask-y.ai/knowledge-di...
"Data engineering is critical because we have the opportunity to have the one human data team."
ask-y.ai/knowledge-di...
Learn more:
docs.rilldata.com/notes/0.77
Learn more:
docs.rilldata.com/notes/0.77
A complete cloud-native FinOps setup in minutes.
🔗 Explore the full walkthrough
A complete cloud-native FinOps setup in minutes.
🔗 Explore the full walkthrough
We also added the ability to generate test data using AI. This is super useful to get up & running in Rill Developer.
We also added the ability to generate test data using AI. This is super useful to get up & running in Rill Developer.
The promise: FinOps Made Easy.
The promise: FinOps Made Easy.
On the new episode of Data Talks on the Rocks, @medriscoll.com and dltHub's Matthaus Krzykowski break down the shift: LLMs are abstracting away complexity in data pipeline building, and the results are dramatic.
On the new episode of Data Talks on the Rocks, @medriscoll.com and dltHub's Matthaus Krzykowski break down the shift: LLMs are abstracting away complexity in data pipeline building, and the results are dramatic.
www.youtube.com/watch?v=ctbG...
www.youtube.com/watch?v=ctbG...
This powerful tool stack combined with dlt's connectors, @duckdb.org and @rilldata.com's interactive dashboards, deliver a real-time, consolidated analytics view.
This powerful tool stack combined with dlt's connectors, @duckdb.org and @rilldata.com's interactive dashboards, deliver a real-time, consolidated analytics view.
Top Takeaways:
- AI has vaporized old advantages - giving sharp builders new leverage
- Classical ML + NLP are coming back swinging
- How to stand out when 500+ engineers flood every job posting
Top Takeaways:
- AI has vaporized old advantages - giving sharp builders new leverage
- Classical ML + NLP are coming back swinging
- How to stand out when 500+ engineers flood every job posting
The project that comes with this article contains incremental import pipelines, models them in metrics, and showcases them as unified dashboards.
The project that comes with this article contains incremental import pipelines, models them in metrics, and showcases them as unified dashboards.
Ex:
- What parts of your codebase have most churn?
- Do some contributors have large commit tendency?
- How does weekly productivity change?
docs.rilldata.com/guides/githu...
Ex:
- What parts of your codebase have most churn?
- Do some contributors have large commit tendency?
- How does weekly productivity change?
docs.rilldata.com/guides/githu...
Thank you Salomon Vaisberg from Drio Tech for highlighting Rill's agentic analytics in your webinar.
www.youtube.com/watch?v=i7dH...
Thank you Salomon Vaisberg from Drio Tech for highlighting Rill's agentic analytics in your webinar.
www.youtube.com/watch?v=i7dH...
AI shockwaves, mass consolidation, & collapsing toolchains have pushed every practitioner back to zero. But Joe Reis flips the script: this isn’t a meltdown - it’s the biggest opportunity builders have had in a decade.
Find the episode here: datatalks.rilldata.com
AI shockwaves, mass consolidation, & collapsing toolchains have pushed every practitioner back to zero. But Joe Reis flips the script: this isn’t a meltdown - it’s the biggest opportunity builders have had in a decade.
Find the episode here: datatalks.rilldata.com
A podcast for the ones that keep building. Subscribe👇
datatalks.rilldata.com
A podcast for the ones that keep building. Subscribe👇
datatalks.rilldata.com