Starburst Galaxy

What do you like best about the product?

I like how easy it is to query data from different sources using SQL. I can access distributed data in one place without moving or duplicating it, and get to the information I need for reporting and analysis faster. I also like Starburst’s performance and flexibility with large datasets, and find the interface fairly straightforward. Once the basic configuration was done, it became much easier to use and maintain.

What do you dislike about the product?

I found the initial setup and configuration a little complex and time-consuming, especially connecting different data sources. Some advanced features have a learning curve, and the documentation could use more practical examples for common use cases. Once I finished the basic configuration, Starburst became much easier to use and maintain.

What problems is the product solving and how is that benefiting you?

I use Starburst to query data from multiple sources in one place with SQL, without moving or duplicating it between systems just to query it.

What do you like best about the product?

Love the added intelligence layer over the data that just not hallucinates and gives the right insights on the same and the Databricks migration is also very smooth.

What do you dislike about the product?

The downside is that it takes some time to understand the concepts and configure it for the users who are new to data and query engines. Better Documentation can also be really helpful.

What problems is the product solving and how is that benefiting you?

The major thing about Starburst that I like is analysing the data, which is spread into multiple sources like data bricks or SQL. The data discovery part of it is really helpful when you try to query it across distributed systems.

What do you like best about the product?

I like that Starburst is pretty easy to implement compared with the operational overhead of querying fragmented data. I can analyze data where it lives without consolidating it first, and run analysis processes in parallel across different locations. I also like the enterprise-grade lakehouse features, including transactions, time travel, and schema evolution, along with unified governance from one place and data mesh capabilities. It helps different team members work with data stored in different places. The setup wasn’t very tough and felt pretty straightforward, though I didn’t set it up personally.

What do you dislike about the product?

I’d like more integrations for different types of data. RBAC-based policies for a particular stream would also be useful.

What problems is the product solving and how is that benefiting you?

Starburst solves our data fragmentation: we have data across different clouds, databases, and formats, and can query it without consolidating it first. That avoids moving data across platforms, a huge engineering bottleneck, and a lot of operational overhead.

What do you like best about the product?

It provides all the advantages of Presto, such as reducing the time required for analysis and making it easier to access data. It can run a single SQL query across multiple different data sources at the same time.

What do you dislike about the product?

Sometimes performance drops with large or complex federated queries. When queries are complex and there are many concurrent users, I notice slowness and overall performance issues, especially when the query involves a large amount of data.

What problems is the product solving and how is that benefiting you?

Starburst helps address the high cost and complexity that come with centralized data challenges. It acts as an open SQL engine, making it easier to work across data sources without adding unnecessary overhead. To me, it feels like a modern approach to maintaining data integrity and providing a solid foundation for AI-enabled solutions.

What do you like best about the product?

I like Starburst’s flexibility, scalability, and ability to simplify data access and analysis. It helps improve efficiency, supports informed decision-making, and provides a convenient way to work with data from different sources.

What do you dislike about the product?

While Starburst offers useful capabilities, there is always room for improvement in usability, documentation, and ease of configuration. A more intuitive experience and clearer guidance could make it easier for users to get started and work efficiently.

What problems is the product solving and how is that benefiting you?

Starburst helps address challenges related to accessing and analyzing data across multiple sources. It simplifies data querying, reduces the need to move data between systems, and helps save time, improve productivity, and support better decision-making.

What do you like best about the product?

As a developer, I’m always looking for new AI-powered software and products. This tool helps me evaluate new options and use them based on our needs. I like the UX because it’s straightforward. It’s also very easy to integrate with Claude Chrome, where I can use an agent to filter out the software I want to review. Overall, it has improved my productivity and performance. From an ROI perspective, it’s been one of my best investments and has been a real support in my research.

What do you dislike about the product?

Honestly, I haven’t found any downsides. I can’t really think of anything negative to point out. It works great for my work and what I need it for, so I’ve never had any complaints.

What problems is the product solving and how is that benefiting you?

Starburst addresses the challenge of accessing, managing, and analysing data spread across multiple sources, without requiring everything to be moved into a centralised data warehouse. Many organisations struggle with data silos, slow queries, complex integrations, and high infrastructure costs. Built on Trino, Starburst enables fast, distributed SQL analytics across data lakes, databases, and cloud platforms, helping teams work with their existing data and get insights from it more efficiently.

What do you like best about the product?

that no data migration is required in central warehouse. Directly, starburst services can be used and data can be instantly query and analyze where it is stored.

What do you dislike about the product?

Unpredictable cost, UI is not so much user friendly and one more thing is when any issue occurs, its pretty much difficult to troubleshoot. Performance and integration is okay but can be improved.

What problems is the product solving and how is that benefiting you?

Queries multiple multicloud and onprem sources simultaneously benefiting in no more waiting weeks for engineering teams to build new pipelines. Secondly, accessing raw data feeds directly at the source in real time helps in faster decision making.

What do you like best about the product?

I use Starburst Galaxy to run SQL queries across different data sources with ease. I love how it allows me to join data from separate systems in a single query without having to move or duplicate the data first. The connectors are incredibly beneficial, connecting several sources and enabling me to query them together. They are also easy to set up, especially when adding a source in Galaxy, which requires very little configuration. Connecting to object storage was straightforward for me, and the built-in query editor is a feature I use the most, as it lets me write and run SQL directly without needing a separate client.

What do you dislike about the product?

The cost. Because billing is usage-based, it's hard to predict what I'll pay in a given month, which makes it difficult to budget as an individual user. Clearer cost estimates up front would help.

What problems is the product solving and how is that benefiting you?

I use Starburst to run SQL queries across different data sources without needing to move or duplicate data, saving steps in the process.

What do you like best about the product?

No data duplication, High Performance, Cost Optimization, Cloud Flexibility, Open Architecture, Data Security, Governance, and Business intelligence integration

What do you dislike about the product?

Query Performance can vary, Complex troubleshooting, Dependence on source systems, Cost management, Not ideal for every workload, connector limitations

What problems is the product solving and how is that benefiting you?

Customer database: Stores customer name IDs, Sales data: Stores millions of order records in files, Product Inventory: Stores product names, stock levels

What do you like best about the product?

The combination of blazing-fast federated query performance and true openness (built on open-source Trino, supporting Iceberg and other open formats) without vendor lock-in.

What do you dislike about the product?

Cost is unpredictable. Consumption-based pricing means monthly bill can suddenly shoot up. Enterprise users say it's double charge license plus infrastructure. Hard to forecast, especially when new users join.

Connectors are hit or miss. Some connectors single-threaded, slow. JDBC bottleneck caps speed around 35MB/s no matter how many nodes you add. Azure Blob Storage not supported. Cross-region querying still in private preview.

Architecture has issues. Single active coordinator means single point of failure. Cluster startup takes 3-5 minutes. No Terraform provider. Rate limits 150 queries/second, 40 concurrent queries per cluster. Queries get queued or rejected during peak time.

Documentation is weak. Too basic for enterprise. Not enough production examples for custom functions, security policies, performance tuning. Sometimes docs are incorrect also. Users waste lot of time troubleshooting.

Ecosystem gaps. Galaxy not tier-1 dbt partner. Lags behind in new dbt features. No built-in orchestration or data processing—need extra tools for full pipeline.

Bottom line: Query engine is powerful, but cost, operations, and integration friction can be headache. Especially if you expect same freedom as self-managed open-source Trino.

What problems is the product solving and how is that benefiting you?

Data silos and slow access. Companies have data scattered across data lakes, warehouses, databases, and clouds. Querying across them meant moving data or building complex ETL pipelines. Starburst queries data where it lives no migration needed.

High infrastructure costs. Copying and storing duplicate data wastes money. Starburst reduces data duplication and lowers storage and processing costs by 45-65%.

Poor query performance. Legacy systems like Hive were slow. Starburst delivers up to 600% faster performance and handles thousands of daily queries with ease.

Slow user onboarding. Manual role setup took days. With Starburst, teams onboarded in 2 hours using group-based permissions.