91–100 of 168 posts
Earlier quoted context omitted.
Do you work for Databricks?
They must do. But if you've been in this area for long enough, I'd put my money on Databricks, if anything, because of their open source integrity
Data Wars: Snowflake vs Databricks (0 - 2)?
Serious question: Databricks, Snowflake, Dremio. All these "Data" platform companies => which one do you have for your Data Lake and Data Warehouse solution? I'm sick and tired of these companies Snake Oiling the Data industry by offering "the easiest" platform to satisfy your Data Lake + Warehouse solution only to fall hard whenever you hook it up with your production data (big dataset). PS: Anyone selling Data Lake…
Please read up on Lakehouse. Data Lake + Merge support + DW performance is now possible. That is the game changer.
As of today, these companies are not good enough to take on the Data Warehouse part.
Earlier quoted context omitted.
They must do. But if you've been in this area for long enough, I'd put my money on Databricks, if anything, because of their open source integrity
Databricks isn't open source, as they keep hold of all the IP that makes it much better than OS Spark. Whether you buy Snowflake or Databricks, you're buying proprietary software.
Earlier quoted context omitted.
In what way is lakehouse architecture beneficial over something like Snowflake or BigQuery? I understand the appeal over having lake and warehouse as separate components, but with those native cloud warehouses, you can already do everything a lake does.
With a datawarehouse, you can only interface with your data in SQL. With big query and snowflake, your data is locked away in a proprietary format not accessible by other compute platforms. You need to export/copy your data to a different system to train an ML model in python or R. With the lakehouse, you can use python, R and Scala, (not just SQL) to interface with your data. You can use multiple compute engines (sp…
As much as I love seeing competition in the space and am enjoying my popcorn, I really don't understand what Databricks is doing here: this feels like a childish foodfight rather than an obsession with the customer...
Yes, the tone of those blogposts, the likelihood of fake benchmarks submitted on someone else's behalf and especially the deluge of new accounts supporting them makes me want to trust Databricks even less than the PoC my company ran with them last year and spending time with their terrible, terrible salespeople. EDIT: I forgot lying about how open they are when all their interesting technologies (like the new sql eng…
I would say that TPC-DS and TPC-H are really table stakes benchmarks for data warehouses at this point in time (maybe they weren't 10 years ago). How to build a database that does well on them is well documented in the literature now[1][2][3][4] (maybe a few other papers). Its not easy to build such a database, but its "just" hard work and many companies have the $$ necessary to do that work. There isn't any magic or…
The public pissing contest is entertaining while also being silly and slightly cringe, but I think it's a nice story for Databricks nonetheless. They now have a performant SQL-based analytics engine that can credibly compete with the best DWs in the market today, and it's just one part of their overall platform.
The sense I get is that Snowflake wants the conversation to be "no matter what you do, you need a data warehouse, and we're the best in the business at that." Databricks' Lakehouse approach is a fundamental challenge to that, and if they're getting this kind of performance from their analytics engine against the market-leading data warehouses today, that's a big momentum shift in their favour.
Earlier quoted context omitted.
They must do. But if you've been in this area for long enough, I'd put my money on Databricks, if anything, because of their open source integrity
Databricks isn't open source, as they keep hold of all the IP that makes it much better than OS Spark. Whether you buy Snowflake or Databricks, you're buying proprietary software.
Earlier quoted context omitted.
Redshift is pretty terrible, stay away. AWS is even worse at delivering promises than Databricks and that's saying something. I heard Google BigQuery is good. It is completely SaaS (like AWS Athena that works). Unicorns often run their own stack and you could replicate that, if you have the apetite. Netflix and Apple run Trino + Spark on k8s + Iceberg. Uber used their own Hudi thing, not sure if they still do.
Apple is a big Deltalake (and Databricks) customer: https://www.youtube.com/watch?v=SFeBJxI4Q98