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starburst Trino performance
What do you like best about the product?
ranger, data mesh, distributed SQL engine
What do you dislike about the product?
tuning is cumbersome to perform some times
What problems is the product solving and how is that benefiting you?
leveraging federated semantic layer feature, helping business users
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Great support and utilities around the powerful Trino engine
What do you like best about the product?
The care Starburst put in the UX clearly shows. Also, their support and knowledge of the engine are great. The updates on the platform are very frequent, and documentiation is easy to use.
What do you dislike about the product?
Nothing, in particular. We still have to understand if the costs will grow too much, but it doesn't look like it.
What problems is the product solving and how is that benefiting you?
Starburst is used as the Data Mesh Query Engine in our company. It allows connecting BI tools and notebooks to analytics engines as well as exploring the operational databases thanks to its federated nature. We are also exploring using it for data transformation processes instead of Spark, for some cases.
Leads to Success in Business
What do you like best about the product?
The product is in constant development. Every release brings new features, performance improvements, and fault tolerance enhancements. It helps keep users happy and productive which leads to success in business.
What do you dislike about the product?
Storing metadata in Hive metastore creates a lot of overheads. It requests the building of dedicated complex infrastructure and troubleshooting in case of any issues might be a real challenge.
What problems is the product solving and how is that benefiting you?
Starburst has replaced many tools and data transformation systems with one unified platform. As a result, it saves time for support and maintenance infrastructure and speeds up the onboarding of users.
I am data Engineering Manager and our team heavily used this tool to meet our business needs
What do you like best about the product?
the features supported and Documentation is very detailed and easy to follow-up
What do you dislike about the product?
Some Error messages are not very clear when we try to integrate with hive database
What problems is the product solving and how is that benefiting you?
they connect with us regularly and collecting the logs and assigning a dedicated technical resource is very helpful for us to get a quick turnaround
Recommendations to others considering the product:
Highly recommend this tool to other teams and other companies
user friendly and powerful data analytic tools
What do you like best about the product?
easy to use and deploy. good tech support.
What do you dislike about the product?
less debug info for cockroachDB exceptions
What problems is the product solving and how is that benefiting you?
our ETL team use this tool to analyze data from various databases
Starburst review from SOPHiA GENETICS
What do you like best about the product?
Regular business meeting, functionality of the product being able to run data queries against decentralized data centers worldwide, great technical support.
What do you dislike about the product?
Pricing policy defined on the deployed resources instead of Starburst usage only.
What problems is the product solving and how is that benefiting you?
Starburst Enterprise enables us to query in single queries and very easily our data from multiple data source formats spread worldwide. Starburst includes access control features allowing us to define in detail data access to our users and services. With Starburst we are able to have data governance over our data using their Data Product feature.
Zalando is a very happy customer of Starburst Enterprise for the last 3 years
What do you like best about the product?
We have found that Starburst Enterprise that is built on the open source Trino project is very easy to use and administer. The default setup and the fact that SEP is choosing the right JVM and cluster configuration based on the hardware setup we use automatically makes it very easy to use for our workload and has very high performance. The response times of the support cases are very low and result fast in resolution. For critical issues, we can get support from the Trino contributors
What do you dislike about the product?
release management is lacking. We were hit by some undocumented breaking changes in the Trino open source project and Starburst Enterprise deployment model that affected our timelines in the past.
What problems is the product solving and how is that benefiting you?
Starburst powers the serving layer of Zalando's data lake on S3. We have more than thousand internal users and 100s of applications using Starburst daily, running 30k+ queries that are processing half a petabyte per day. Starburst is connected to many different BI tools that power dashboards and drive Zalando's business and internal KPIs
Starburst Enterprise deployment
What do you like best about the product?
The customer success team (Technical Account Team) are super helpful. The Starburst tool has many connectors and supports industry-standard tools like DBeaver and DBVisualizer so it's easy for customers to use to realize value almost immediately. It speeds up the analytics up to 80% so ad-hoc queries can be performed quickly and efficiently.
What do you dislike about the product?
The amount of customization needed to achieve optimal settings. Paying for the technical account manager is a must to achieve optimal efficiency for the tool. Support is helpful but they don't understand all the customization that's done so that's where TAM will provide additional value.
What problems is the product solving and how is that benefiting you?
Our big data environment is slow and Hive performance is inadequate. Starburst speeds up the query speed for our customer base (>100 analysts) up to 80% and also allow customers to perform cross-platform queries (Big Data and SQL Server) together without having to copy data.
Starburst has helped us to change the way we work
What do you like best about the product?
Strong product features which helped us to join disparate data sources across different clouds and territories. Also, it helped us to do things a lot faster than we used to do.
What do you dislike about the product?
Not much to say but having an automated data cataloguing feature will definitely be nice.
What problems is the product solving and how is that benefiting you?
Like any other business, we have disparate datasources that reside in different clouds and on-prem. Previously, it was difficult to quickly answer business questions but after Starburst we can connect data sources together without moving any data. Now, it is quite easy to answer any business queries.
Recommendations to others considering the product:
If you have trouble with disparate data sources which slows you down in answering business queries or going to market quicker. then Starburst is the right product for you.
Data Mesh / Data Virtualization Realized
What do you like best about the product?
Starburst Data Enterprise Trino is a solid solution to enable ad-hoc analytics and cross-platform data join capabilities. It supports both on-premise and the cloud, dozens of connectors, and levels the playing field for folks looking to work with Big Data (without being a Big Data engineer!). It's simple and easy to use, with most folks able to jump right in with high school-level knowledge of ANSI SQL. Performance meets or exceeds most expectations, and we see significant performance gains over technologies like Apache Hive for querying time and efficiency.
What do you dislike about the product?
There's not much to dislike here. On a rare occasion, you may run into "bleeding edge" issues and need to wait (usually not too long) for edge cases to be addressed.
What problems is the product solving and how is that benefiting you?
I'm currently using Starburst to make it easier for users to perform cross-platform joins (between data types/technologies), lower the barriers to entry for data exploration, support production-grade ad-hoc analytics, and move in the direction of a data mesh architecture. We have realized benefits in the form of faster processing times, reduced data transfer over the network, and reduced data duplication/storage, resulting in both cost and time savings.
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