I've setup a few (more or less standard) data warehouses in Redshift. Prefer SQL for data exploration. That being said, I've used GDS for a few months now, and

I've setup a few (more or less standard) data warehouses in Redshift. Prefer SQL for data exploration. That being said, I've used GDS for a few months now, and it has a lot of mid-market potential, since it pulls data from Google Analytics, Adwords, & Youtube out of the box, and, is completely free. I say "mid-tier" because, for large-scale but relatively simple use-cases (I work on a v. large e-commerce site for a large multi-national, some scale but not the most complex setup I've worked with). While you're "in the ecosystem", you're abstracted from a number of complex issues, like data quality, ingestion jobs, ETL, normalization, etc. HUGE deal for a lot of folks transitioning "into the big leagues". Commercial-off-the-shelf solutions for a lot of the products companies use are supported by the big ETL startups (Fivetran, Alooma, Stitch Data) to BigQuery. I think their long term goal is to get these mid-tier folks in and standardized on BigQuery. In the future this may become more competitive with Redshift. It makes sense. They own the bottom tier. Every team gets started these days by getting good at Google Analytics. Then they outgrow it, and move "out of the ecosystem". Eventually, they may be able to build out an ecosystem around BigQuery for data scientists and data science teams, but filling that gap could make them a ton of money. UX isn't quite where I would like it, but it's getting better. Some small details make the interface confusing, but that's par the course in this domain. 1/ Getting data in is fine, but you're using BQ. Personal preference that is not my favorite tool. 2/ To my knowledge Google Cloud offers the same guarantees and promises as AWS 3/ Authoring is very easy. Perhaps too easy (I would say this is probably one of the best mid-range tools for data vis. I wouldn't say it wins on a feature-by-feature comparison to PowerBI or Tableau). 4/ Partial (limited extent, but w/o writing SQL) 5/ Partial, but not to the extent you would want in a paid tool in this category. Again, no SQL (this is probably a win for some folks, and a minus for others) 6/ Yes. Although it's more like Filters on a whole dashboard or multiple pages of reports in a project. 7/ I've done custom binning, trailing time periods, pretty much everything I would do on a routine basis for data exploration. However, there's no SQL chart authoring, so I wouldn't be surprised if there's something I'm missing here. --- Bottom line, if you're mid-tier it's a great free tool to try, especially if you're just a data scientist looking to do something fancy for a Marketing team with Marketing data, who hasn't really been exposed to rigorous analysis in the past. You could easily do the type of exploration to make good decisions about building an attribution model, for example. Would meet the needs of 99% of companies I've consulted for, if it wasn't for BQ vs. Redshift.