Hello Hunters! -- I'm Mike, one of the founders of Summer.
We love data. We don't love the price gouging, endless tooling, and complicated integration work it takes to get a simple data stack up and running. We bet you don't either, and thats why we built Summer.
We're on a mission to make data a pleasure.
With Summer, you get:
🚅 Built in ETL. No extra charge, fifty connectors available today, hundreds more in the works.
🕵🏻♂️ Blazing fast DuckDB powered warehouse.
📊 Full analytics suite included. No seat restrictions, bring as many team members as you want.
🤖 AI assistant to help craft queries and charts if your SQL is a little rusty.
🎁 Comprehensive permissioning so you can easily share queries, dashboards, or even raw tables with whoever needs to see them.
We're just getting started and there's more to come.
@admiralrohan definitely! By data stack we mean all the tools your business needs to analyze the data their business creates. The core layers are:
ETL (extract, transform, load) - allows you to pipe data from your source to Summer, i.e. Stripe to Summer or Google Analytics to Summer
Warehouse - this is where your data is securely stored and organized, it is also the Query engine that allows you to analyze your data
Analytics - these tools allow you to write Queries, build Charts, and create Dashboards so that you can analyze your data, visualize your data, and share/collaborate on the analysis with your team
The core use case we are targeting is, a business (likely technology/application space) who needs a data stack so that they can analyze data from their entire business to make decisions about their products and/or services.
Hope this helps, thanks for the question. Here's a doc on our site that goes a little deeper, please let us know if you have any other questions.
@andrew_jameson111 the biggest difference at the Warehouse layer is because DuckDB is so powerful and lightweight our Warehouse is truly ephemeral and requires no management by our users. You can control the access for every Dataset or Table but you don't have to choose deployment sizes or commit to certain levels of throughput.
Summer
Hello Hunters! -- I'm Mike, one of the founders of Summer.
We love data. We don't love the price gouging, endless tooling, and complicated integration work it takes to get a simple data stack up and running. We bet you don't either, and thats why we built Summer.
We're on a mission to make data a pleasure.
With Summer, you get:
🚅 Built in ETL. No extra charge, fifty connectors available today, hundreds more in the works.
🕵🏻♂️ Blazing fast DuckDB powered warehouse.
📊 Full analytics suite included. No seat restrictions, bring as many team members as you want.
🤖 AI assistant to help craft queries and charts if your SQL is a little rusty.
🎁 Comprehensive permissioning so you can easily share queries, dashboards, or even raw tables with whoever needs to see them.
We're just getting started and there's more to come.
Can you explain in more layman terms? What is meant by data stack? What is the use case for this?
Summer
@admiralrohan definitely! By data stack we mean all the tools your business needs to analyze the data their business creates. The core layers are:
ETL (extract, transform, load) - allows you to pipe data from your source to Summer, i.e. Stripe to Summer or Google Analytics to Summer
Warehouse - this is where your data is securely stored and organized, it is also the Query engine that allows you to analyze your data
Analytics - these tools allow you to write Queries, build Charts, and create Dashboards so that you can analyze your data, visualize your data, and share/collaborate on the analysis with your team
The core use case we are targeting is, a business (likely technology/application space) who needs a data stack so that they can analyze data from their entire business to make decisions about their products and/or services.
Hope this helps, thanks for the question. Here's a doc on our site that goes a little deeper, please let us know if you have any other questions.
@summermike Thanks. Got it.
DuckDB-powered stack sounds promising! How does it compare to traditional data warehouses?
Summer
@andrew_jameson111 the biggest difference at the Warehouse layer is because DuckDB is so powerful and lightweight our Warehouse is truly ephemeral and requires no management by our users. You can control the access for every Dataset or Table but you don't have to choose deployment sizes or commit to certain levels of throughput.