According to Jason Kehl, SVP Engineering and Data Science at Vectra, we built a platform that lets data teams “take a load off of engineering. [Teams] don’t have to become experts in Trino or experts in managing Trino. Instead, [they] can focus on business needs.”
But we didn’t want to stop there.
The problem with being all-in on centralization
Since we started building Galaxy, we’ve had hundreds of conversations with data teams about the many challenges they face with their architecture. One pain in particular kept popping up time and time again even among teams that were attempting to centralize on a data lake or warehouse – data silos.
We saw that, despite best efforts to centralize, new data sources (and applications) are constantly being added to tech stacks which means data teams need to layer on new technologies to adapt their current stack to the new data’s needs. Obviously, this only leads to more disparate systems and more data silos.
Given that Trino is built to query exabyte data lakes and data warehouses alike, we saw an opportunity to take Galaxy one step further.
The solution – a data lake analytics platform
After months of work, we are excited to unveil Starburst Galaxy as a data lake analytics platform that’s built for analyzing large and complex data sets in and around your cloud data lake.
You can think of Starburst Galaxy as a single platform where you can discover, govern, analyze, and share all of your data. And the best part? You can do all of this while maintaining ownership over how and where your data is stored.
Starburst Galaxy is made up of three key components:
- A single point of access – Access all your cloud data source, across regions and clouds
- An analytics engine – Execute interactive and batch workloads at any scale
- Gravity – Discovery, govern, and share all your data from a single location
Teams have already started to adopt Starburst Galaxy’s approach and have seen the benefits:
“Starburst Galaxy’s speed and agility has been crucial to helping us scale up our operations. In our BI workloads, we’ve seen queries that used to take 45 minutes execute in under minute. And, for our data science and data analyst teams that want to get their hands on the data, it’s very easy to attach individual compute resources to those workloads without a bunch of manual tuning.”
– Simon Thelin, Lead Data Engineer at 7Bridges
“Other vendors were trying to explain how we had to change what we had to fit into their model. Starburst worked with our architecture.”
– Current Starburst Galaxy customer
Try Starburst Galaxy out yourself with our free tier today.
We also invite you to join us June 20 – 23 for Galaxy Launch Week – an entire week dedicated to what’s next in data lake analytics. New features, new tutorials, and new swag. Galaxy launch week has it all.
Try Starburst Galaxy today
The analytics platform for your data lake