I'm launching the London Observability Engineering, and I’m scheduling speakers and topics right now, so if you have something to share about Observability, I'd love to speak to you!
Here are a few topics I'm thinking of covering:
Next-gen instrumentation with eBPF & OpenTelemetry, GenAI in Observability, implementing observability for legacy systems, API observability, and data observability.
The reality is that RPA, AI, ML, etc ... are still years away when it comes to the industrial sectors (e.g. manufacturing, energy, oil & gas, etc).
Sure there are many PoCs, smaller projects, but in my experience, working on data centric projects with a few fortune 500 industrial companies, none of these technologies have been successfully implemented in production.
Perhaps for some back office & business-level applications, but certainly not for any production related use-cases (e.g. predictive maintenance).
Karim from Memgraph here. We just launched a project we've been toying around with for a while now, called Memgraph Playground.
The initial idea was to let anyone to learn Cypher (a popular graph query language) and get an idea of what it's like to work with graphs without any friction:
- In-browser experience. No downloads required.
- No sign up required
- Preloaded datasets with many more to come
- Step-by-step tutorials with example queries & explanations
The project is still in the early days, and we're planning to add more functionality, but for now you can:
- Run read Cypher queries only. Wright queries aren't supported
- Run some popular graph algorithms (Breadth First Search, Weighted Shortest Path). We'll be adding many more.
- Visualize your results as a graph or in a table. We'll be adding more styling options.
I hope you find this tool useful and fun. If you have any suggestions or questions please drop them in the comments below.
There is huge potential around better data usage & analytics in agriculture & crop science. You're domain expertise would place you in a unique position compared to other data scientists with more of a generic background.
I've personally spoken to a few large enterprises in the agricultural sector who are just beginning to build out their data science department. It seems like the industry as a whole is just getting started in data science.
Also, there are many promising startups that are emerging in space. E.g. Vertical farming
One of the biggest changes in our latest Memgraph 1.2 release, was the addition of Bolt v4 and v4.1 support.
We thought that it would be interesting to discuss the Bolt Protocol for those of you who are interested in graph databases, and explore what goes into being wire-compatible with another database system.
Please let us know if you have any questions. We're here to help.
Dgraph is actually very different on many aspects like data model, query language, even overall focus & target use-cases.
In my opinion it will be tricky to have a fair comparison. You can have a look at the benchmarks they published against Neo4j. It seemed like there was a lot of disagreements on both side.
What other graph databases would you like us to have a look at?
That's a good point. Benchmarking different systems is always tricky to get right, but we'll get something out soon.
The focus of these benchmarks was to explain to our existing community how we improved things and share with the broader software engineering community has worked for us in the hope it could help others working on graph projects.
We've just released this blog post exploring some of the changes we made over the past few years that helped us reduce memory usage by as much as 50% and improve throughput towards near-linear scalability.
I'm launching the London Observability Engineering, and I’m scheduling speakers and topics right now, so if you have something to share about Observability, I'd love to speak to you!
Here are a few topics I'm thinking of covering:
Next-gen instrumentation with eBPF & OpenTelemetry, GenAI in Observability, implementing observability for legacy systems, API observability, and data observability.
What else should we talk about?