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Great for complex queries
What do you like best about the product?
I like to see how Starburst makes it easier to link disparate data sets. Despite this, it keeps working, running smoothly, and maintaining standard and precision in every organization even when dealing with different environments. The use of research has helped in minimizing the risks posed by incomplete and other mismatched data results. The flexibility it has shown in dealing with the different types of queries it receives has helped minimize on overly complicated intra-functional work flows while directing more effort to the production of relevant results.
What do you dislike about the product?
One major inconvenience of Starburst is that during heavily utilized periods, when executing complicated queries, it draws a rather large number of resources, and hence can be slow. Because fixing these queries involves some high level of technical experience, the problem solving would take a lot of time consuming time than required hence the disruption of the normal working progress hence affecting time bound projects that would be very crucial in the achievement of business objectives.
What problems is the product solving and how is that benefiting you?
Starburst has addressed the problem of having different sources of data where the user has to develop different pipelines to handle them and this has reduce a lot of time and energy. It relieves our team of managing infrastructural issues that would otherwise distract from creating the desired impact. The search and handling of data from different sources have become easier and efficient due to Starburst making our outcomes more accurate and our programs more on schedule.
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Our team’s data access has never been easier
What do you like best about the product?
The thing that I like most about Starburst is that it gives you instant access to all kinds of data across all sorts of places without ever needing to move the data physically. The ability for us to pull insights directly from where the data lives greatly benefits our workflow. By not having to manually collect, transfer, or aggregate data before using it, we’ve been able to streamline our processes and save us a lot of very valuable time.
What do you dislike about the product?
In sum there are many good things with Starburst search engine but it is not always suitable for task of executing very specific, detailed questions. In some cases when a certain level of depth or specificity is required for business operations we have had to turn to other tools. Sometimes this longer process can be quite bothersome, especially when one has to shift between the tools for the purpose of the different interfaces.
What problems is the product solving and how is that benefiting you?
Starburst helps us solve one of its main challenges – use of dataset across multiple platforms for analysis becomes challenging. We found ourselves daily shuffling and merging data without the use of It which was greatly involving and full of errors. Now with Starburst we can go direct to where the data sits and it has helped to do a lot of these things for us, so we are more efficient and pretty much get accuracy in our working which has led to making quicker decisions.
Finally querying data from different sources feels effortless
What do you like best about the product?
I like Starburst to be able to let us query data from various sources but we don’t need to bring everything into one central database. It doesn’t matter it is AWS, Snowflake or other data platforms as we can work with data from multiple systems simultaneously. It saves ourselves from the extra steps like data transformation or migration and makes us to focus on what we should and actually need to do. It’s a big time saver and it makes it easier to streamline the processes.
What do you dislike about the product?
The problem with Starburst is permissions and access control across multiple data sources. There’s no central place to manage the permissions of all platforms. And each system has its own security protocols. The simple implication is that there’s a lot of elements we have to log into separately to make the changes that we need to. It’s an extra step that can throw off workflow, and especially when working on several platforms, with different user access needs.
What problems is the product solving and how is that benefiting you?
With Starburst, you have solved the problem of accessing and working with data that resides in multiple systems. Until that point we had to merge datasets manually, which was slow and error prone. With Starburst, we have eliminated a lot of time and the potential to slip up by allowing us to query the data that we're getting from AWS, Snowflake, and so forth directly. This efficiency has freed us more time to spend our analysis and decision making.
For us it's a real game changer for data querying
What do you like best about the product?
I enjoy most about Starburst the ability to increase the overall speed and accuracy of how we retrieve our data. The platform ensures that whatever we're looking for pulls up instantly, and correctly. With this efficiency, my team has more time to actually thing about a problem instead of wasting time browsing for data. We’ve found it very smooth on the data management side, making our processes much smoother, and bringing a lot more productivity to them.
What do you dislike about the product?
Starburst is a challenge if you have a lot of users, and a lot of them are accessing it at the same time - it can become slow. However, there is a occasional lag disorientating on workflow mostly when we are about to have access to the data quickly. The platform is too unstable during peak periods. It happens when we can’t do things on time, and when we can’t, we need to start over with deadlines.
What problems is the product solving and how is that benefiting you?
Starburst has found a much more efficient way to solve the problem of how to access data across many different systems. Before, we did spend a lot of time moving between platforms to package and potenially pull data manually. Finally, now we can get everything we need from a single place, maximizing our time and working a lot quicker. Also, the integration of various data sources into one platform has allowed us to run reports, and make quicker decisions.
Efficient query handling for large datasets, best I ever used
What do you like best about the product?
I specially like that Starburst has an exceptional performance managing complex queries over large datasets. What that platform is fantastic with is processing huge quantities of data quickly so when we want to do detailed analysis, we don’t have to worry about slow downs. It's especially helpful when we're dealing with highly complex queries that span different databases. Querying without needing to physically move the data saves a lot of time and resources.
What do you dislike about the product?
While Starburst can be resource intensive with large or complex queries especially. Although it does well with data, when at peak usage, some queries might be slower to process or consume more resources than they should. By doing this however, we end up with delays, particularly when we want to be making analysis out of the real data in real time, or delivering insights immediately, which is very undesirable in a fast pace environment.
What problems is the product solving and how is that benefiting you?
Starburst is a solved problem to querying across multiple platforms without the need to consolidate everything in one place. This has speeded up our analysis process to the point where we can run complex queries on disparate data sources such as databases on cloud and on premises. It helps us make more informed decisions faster, get insights, save us time and we spend less resources getting those insights which in turn enhances our operational efficiency.
Now data workflows feel more streamlined and effective
What do you like best about the product?
What I love about Starburst is how easy it is to query data across multiple data sources. Either way, we use it to run complex queries across our cloud data warehouses and on premises systems without having to think about the data silos. We’ve seen seamless integration with tools such as AWS Redshift and Google BigQuery which has meant our team can access and analyse data much quicker. More specifically, it is most useful for running analytics at scale to allow us to make data driven decisions faster.
What do you dislike about the product?
Starburst’s one downside is that it doesn’t perform well for very large datasets. It does a great job most of the time, but if you have an unusually large dataset it can slow things down. It has meant that we’ve been unable to get real time insights on some of our more complex queries. This can be costly and time consuming to fix and is not good for businesses that run on tight budgets.
What problems is the product solving and how is that benefiting you?
The problem of access and Analysis of data from multiple sources in real time has been solved by using Starburst. With it, we can seamlessly query both cloud and on premises data systems without concerning ourselves with moving data around or with silos. It has saved us time, improved coordination between departments and expedited our decision making process. Running complex analytics without having to worry about data incompatibility is particularly useful for it.
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.
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
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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