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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.
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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
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.
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