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Starburst Enterprise Review
What do you like best about the product?
We originally had our data lake built on a Hive engine. One of the tings we like about Starburst Enterprise is the improvement it provided to our consumers by providing a powerful distributed SQL query engine built on a Trino engine, allowing fast querying across diverse data sources.
We also shifted away from an Enterprise Data Lake secured Privacera Ranger to a Data Mesh architecture governed by AWS Lake Formation. From a business and customer support perspective, Starburst were attentive to our technical/business requirements, feature requests, etc.
We also shifted away from an Enterprise Data Lake secured Privacera Ranger to a Data Mesh architecture governed by AWS Lake Formation. From a business and customer support perspective, Starburst were attentive to our technical/business requirements, feature requests, etc.
What do you dislike about the product?
One area of improvement for Starburst is to consider the rollout of GA features after undergoing somewhat further rigorous/comprehensive use case testing. Or alternatively, perhaps be more mindful with the language of GA vs Public Preview vs Private Preview.
What problems is the product solving and how is that benefiting you?
Starburst is providing our consumers a seamless and easy method to; scalable, high-performing, cross-data source federation solutions for many of their use cases. With our analytics community being empowered to continue developing more efficiently and productively, this overall reduces the time to market business impact
1) Cross-data source federation: Allows querying across multiple data sources simultaneously, including databases, data warehouses, and data lakes.
2) High performance: Optimized for fast query execution on large datasets through features like intelligent caching and query optimization.
3) Scalability: Can scale horizontally to handle growing data volumes and concurrent users.
1) Cross-data source federation: Allows querying across multiple data sources simultaneously, including databases, data warehouses, and data lakes.
2) High performance: Optimized for fast query execution on large datasets through features like intelligent caching and query optimization.
3) Scalability: Can scale horizontally to handle growing data volumes and concurrent users.
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Starburst as query engine with modern gdpr comliant datalake
What do you like best about the product?
Super easy to manage.
Good query editor.
Responsive autoscaling with good performance in query execution.
Support for different datasources and federated query execution.
Great customer support.
Easy to implement and start using starburst galaxy.
Good query editor.
Responsive autoscaling with good performance in query execution.
Support for different datasources and federated query execution.
Great customer support.
Easy to implement and start using starburst galaxy.
What do you dislike about the product?
Catalog features are still basic and lack certain functionalities.
Its a lot of manual effort to maintain access policies as we have to add each schema/table while creating policies.
We are missing AI features to convert text to queries, optimize certain queries etc.
Its a lot of manual effort to maintain access policies as we have to add each schema/table while creating policies.
We are missing AI features to convert text to queries, optimize certain queries etc.
What problems is the product solving and how is that benefiting you?
We are using it as query engine to read data from datalake and use it in for creating analytical usecases in the company. We use it from our BI tool MicroStrategy and data discovery tool/catalog Alation.
Fast and no hastle
What do you like best about the product?
How easy is the implementation, use and maintenance
What do you dislike about the product?
Would be good if it had better 2FA implementation
What problems is the product solving and how is that benefiting you?
Analysing big data
Easy to implement and manage, security documentation from vendor side could be better.
What do you like best about the product?
Easy to implement an manage, customer support is very responsive/knowledgable.
What do you dislike about the product?
Documentation on best security configuration practices could be better.
What problems is the product solving and how is that benefiting you?
Improving query performance and I would say reduces our costs.
A versatile platform with robust query capabilities
What do you like best about the product?
What I really like about Starburst is how much better it makes managing our scattered data. And we’ve integrated it with S3 and Snowflake to move data in a way that’s not manually moving data. This is incredibly user friendly, and enables us to run SQL queries with minimal hassle which saves us so much time. And just its broad feature set one in particular is that its real time queries ability also keeps our work flows efficient and responsive.
What do you dislike about the product?
Starburst’s biggest drawback, for small teams that are scaling, is the cost. It’s also a little more technical to setup and configure than some teams have readily available expertise for. Some of our projects have slowed down due to these challenges as we become more dependent on IT help. While it’s well integrated it can be more complex from a technical perspective so onboarding new team members can take longer and be more difficult.
What problems is the product solving and how is that benefiting you?
Breaking down data silos is one thing I love about Starburst, because we can query multiple sources all in one place, e.g. Google Cloud and on premises databases. We’ve spent tons of time manually merging data and it’s saved us that time. It’s easy to manage the large datasets because of its smooth integration and features like the SQL based system. This has been a game changer to decision making as it helps us make decisions across departments more efficiently, and work quicker on complex analytics.
Simplifying complex data integration for faster insights
What do you like best about the product?
My all time favorite thing about Starburst is its ability to rapidly query data from multiple sources. Through integration with tools like AWS, Google Cloud and Snowflake we can run complex queries without having to move the data around. Intuitive interface makes it easy for teammates of disparate technical levels to get going. This is fast – perfect for querying a huge dataset that has made our data analysis process very efficient.
What do you dislike about the product?
Starburst is not without its flaws – it can take quite a while to learn during the setup phase making it a very steep learning curve. Everything needs to be configured correctly and it might be difficult for smaller teams to manage. Also its pricing tends to be difficult for smaller businesses with limited budgets since as the query volume increases, the costs rise further, rendering it less budget friendly for teams that want to scale cheaply.
What problems is the product solving and how is that benefiting you?
With Starburst, the need to move data between platforms has been eliminated, eliminating the hassle and delaying the analyzing of information. It has simplified cross department collaboration and sharing of data by integrating with tools like AWS and Google Cloud. We found this has helped us make better decisions faster, spent less time getting and stitching together data. All up, it’s been an overall more efficient and productive workflow.
Reliable performance for large-scale data management
What do you like best about the product?
My favorite thing about Starburst is its awesomeness at querying data from multiple sources without having to move or transform data into a central repository. This saves us huge amounts of time and resources. It works with platforms like Tableau and Apache Kafka thus making our data visualization and real time analysis. We have been able to quick query large datasets with its efficient distributed query engine, increasing our team’s productivity.
What do you dislike about the product?
A disadvantage of Starburst is that execution often requires resources in some cases it affects the general performance of the system particularly when retrieving data on large scale. This has caused some delay at times that hampers quick analysis primarily during high traffic usage occasions. Also, to set it up and fine tune it for sophisticated searches needed some real heavy work and knowledge, which could sometimes be a problem for teams without applied data scientists.
What problems is the product solving and how is that benefiting you?
Starburst solves the problem of stored data being in silos by making available to us the ability to access and query information within different data sources without doing complex ETL. They’ve certainly greatly benefitted our workflow by offering fast and unified insights, and thus faster data driven decisions. It has given our teams the ability to work more effectively, minimises reliance on centrally maintained data warehouses and shortened our reporting time, reducing our overall operational efficiency.
Powerful data querying across multiple platforms
What do you like best about the product?
I really appreciate how Starburst keeps everything very simple to access and analyze data from all the different data sources and it’s all in real time. Integrating with cloud data warehouses like AWS Redshift and Google BigQuery means that we can work faster and can concentrate on figuring out insights rather than connecting. It enhanced our overall data, from the duplication to moving to data, and overall data workflow and productivity.
What do you dislike about the product?
Starburst has great functionality and whilst lots of people find it helpful, it has some performance issues when dealing with very large datasets. And setting everything up was more complex a challenge than anticipated, especially so when I considered integrating all the data sources. Our analysis was slowed down by the fact that at times the software lagged when running complex queries. Also, it can sometimes be difficult to resolve performance issues if not someone with knowledge on the system.
What problems is the product solving and how is that benefiting you?
Starburst eliminates the problem of scattered data and slow data search over different platforms. Centralized data queries eliminate data transfers or replication and allows by means of it. What that has accomplished is slipped data analysis into our workflows, freeing up more time for us as a team to work on actionable insights. The business has been revolutionized by our ability to easily gain access and analyse data from a multitude of sources and implement a decision.
Really powerful analytics for large datasets
What do you like best about the product?
The thing that stands out about Starburst for me is how it enables querying of large datasets across all platforms, with no need for data movement. This makes analytics on distributed data sources so much quicker. I find it very convenient that is connects seamlessly to our data warehouses, and allows to extract data from different systems to analyse. The ability to work with queries of any complexity has made it a core tool for our analytics.
What do you dislike about the product?
In my view, Starburst has a major drawback - it is complicated when you are first launching it. The adoption of the architecture can be challenging, especially for organizations’ whose teams are not conversant with distributed data systems. Furthermore, it gives relatively slow results if many users simultaneously perform computations, and we have experienced lateness in the processing of numerous important inquiries. This has also hindered decision making in some ways over the years particularly when the organisation is trying to adopt a new data source urgently.
What problems is the product solving and how is that benefiting you?
The primary pain Starburst helps to address is the existence of data distributed across different platforms which must first be joined to perform analyses on. The greatest improvement we achieve with Starburst is in query flexibility, which eliminates the need to perform several requests to multiple systems at once, thereby reducing infrastructure costs. To relate the improvements in the decision making process and how it has supported team work through the simplification of access to information and increment in the precision in our analytical work.
Great reliable solution for handling complex data queries
What do you like best about the product?
For me, what makes Starburst unique is that it runs large analytical queries from multiple data platforms with no performance penalty. It is relatively easy to integrate work with other programs, such as Power BI and Tableau, and that saves time on implementation of tools. Consequently, due to the numerous features that make it easy to use, we do not have to necessarily use other tools frequently in my line of work to realize how much it improves our data processes.
What do you dislike about the product?
I do not like that at times Starburst is costly and this may be problematic for a small team or business. The software is capable of producing simple and effectively outstanding features with no additional cost, but this utility can be difficult to market when you are not operating on a large scale. This changed our budget, and we had to wonder if we could still use it as a long term solution. On the plus side it has loads of features for the price, but which makes it unsuitable for smaller applications.
What problems is the product solving and how is that benefiting you?
Starburst solves the problem of having to work with many data sources individually yet interrupts all this with the power of all in one without having to integrate them manually. It helps to simplify our work and makes the analysis faster. It has improved productivity because we do not spend time transferring between applications, and our work partners can quickly obtain important information and make more precise business decisions.
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