[kthejoker2]

Strong concur, the idea of "database" just doesn't make sense anymore, I've (d?)evolved to "storage, streaming, and compute" (as it seems you do as well) in all my discussions.

Have you read ThoughtWorks material on the "data mesh"? Sounds like your product is looking to be a part of that kind of new data ecology.

https://martinfowler.com/articles/data-mesh-principles.html

It is in definitely anticlimactic after data warehousing, data lakes, data lakehouses, etc. to just throw up your hands and say "data whenever you want it, wherever you want it, in whatever form you want it" (at whatever price you're willing to pay!) So I feel your pain on marketing your product,but I think the next 5 years or so will be heavily focused on automating data quality and standardized pipelines, computational governance and optimizing workloads, and intelligent "just in time" materializaton, caching, HTAP, etc.

Your big play in my mind is helping customers optimize the (literal financial) cost/benefit tradeoff of all those compute and query engines.

[snidane]

Can somebody explain Data Mesh in simple terms? I've watched numerous videos and read the article, but still can't understand what it's supposed to say.

Is it basically to set up one data lake per analytics team, instead of a big centralized data lake?

It seems to me this is already being done from my experience. Each team has their own s3 bucket in which they store their data products and other teams can consume them using their favorite data engines as long as they can read parquet files from s3.

Or am I missing something?

[benstopford]

It's basically a set of 4 principals or best practices: 1. decentralized data ownership. 2. Data as a product. 3. Self-serve data infrastructure. 4. Federated governance. So I don't think of it as some new product thing but rather principals that work well for people with a certain type of use case. It's a bit like Microservices in that regard.