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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.
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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.
Efficient solution for data queries across multiple sources
What do you like best about the product?
When it comes to what I like most about Starburst, I believe that one of the greatest benefits is the ability to run highly complicated queries on many data sources simultaneously, and the fact that it can do it without having to shuffle the information. This makes our analysis work much easier. Integrating with reporting tools like Tableau improves our reporting by adding rich visualization on top of the provided data. The ability to quickly and effectively process complex questions further enhances the value of detailed data analysis.
What do you dislike about the product?
The only issue that may be associated with using Starburst is the relatively high cost structure that may not be sustainable for teams and businesses of a moderate size. Due to this, it becomes quite challenging to justify the cost against the benefits that come with using this device. Additionally, although it is robust in many ways, there is always the issue of slow query speed when dealing with very large datasets. This occasional lag can cause havoc for data analysis and decrease the overall efficiency.
What problems is the product solving and how is that benefiting you?
Starburst has revolutionized the manner in which I am able to process data from various sources as an organization. Before, consolidation of data was time consuming but today the queries that would have taken a lot of time can easily be run across different databases. It has enhanced effectiveness and expedited decision making. Another advantage that has emerged from interconnection with BI tools for additional reporting is the enhanced refinement of the strategic plans and analyses of data.
This advanced query engine significantly improves data analysis
What do you like best about the product?
In my perspective, probably one of the potent aspects of Starburst is its powerful query engine since it offers broad queries for big streams of data and inquires from many sources. It has been quite useful to compile data from a number of data bases into one and easy to analyze from the same platform. Since it interconnects with data warehouses and BI tools, we can generate vast reports and analyses without moving much information. This has enhanced our decision making as well as operations in general.
What do you dislike about the product?
Starburst eliminates the issues associated with data discovery and management for large scale analytics and queries since it is a single platform that serves as a powerful data processing tool. It has been possible to create summative reports and analyses that would have otherwise required amalgamation of data across various systems. Consequently, our team can quickly make more effective decisions, thus improving the general team performance and strategy development.
What problems is the product solving and how is that benefiting you?
Starburst serves to fill the gap of data access and processing from multiple sources by offering a single complex data analysis solution. This capability has helped in creating greater reports and analysis that do not require the need to pull data from various systems. Therefore, the team can respond quickly to problems and opportunities and make more sound decisions, thus increasing organizational efficiency and effectiveness of the strategic management process.
Unified data queries significantly enhanced our productivity
What do you like best about the product?
I think the most useful function of Starburst is its capacity to query several sources at once. What makes it stand out is that it excels particularly well with big data, which eventually allows for quicker processing. How it connects to other applications such as Tableau for dashboards and Apache Kafka for real time data feeding improves our total effectiveness. I have found this unified approach to data management as a marked improvement in our analytical functions.
What do you dislike about the product?
The main downside is that Starburst may become resource intensive, which results in some implications for performance with very large data sets. This can hamper our analysis and the overall productivity of the workflow. Furthermore, system setup and configuration is not very intuitive and this has made initial training time long for new users. Sometimes these issues have led to a decline in our productivity and more effort was needed to handle them.
What problems is the product solving and how is that benefiting you?
Starburst eliminates the challenge of dealing with an array of data sources and querying through unified software. This has helped us in analyzing our data in a faster way as we can now integrate datasets from different systems into one easily. In terms of benefits the unified approach has to offer, we have noted that it has enhanced our efficiency as more insights can be produced and more decisions made within less time. All in all, it has helped in improving the capacity to meet quick business needs and opportunities.
Complex queries aren't problem anymore
What do you like best about the product?
The most appealing aspect of Starburst in my opinion is the ability to have all the data in a single query layer. This makes its based on SQL interface ideal for complex query across numerous systems without overburdening by the data. I appreciate its ability to work alongside our current data structure, and the real time nature of the data obtained from it. This has improved the effectiveness of the analytical work we do and how we make decisions.
What do you dislike about the product?
Starburst is not as optimal as it could be when used on data sets of very large sizes. It is common for the query to be processed for more time than is desired by the user, a condition that affects the efficiency levels. Further, while the SQL interface is rich, novices will find difficulty in using it for they will have to learn SQL to perform operations. These have almost at one time given rise to problems that include latency and sometimes necessitated additional time to enhance query performance .
What problems is the product solving and how is that benefiting you?
Starburst is the solution to the problem of consolidation and all data from different sources into one convenient platform. This has been highly beneficial in the organization because it makes the querying and analysis of data from various systems easy. It has provided flexibility in terms of achieving greater productivity, faster and with better decision making by allowing real time data processing. It also decreases the required amount of data preparation, which helps us to concentrate on the analysis.
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