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How Starburst compares
Reduce your cloud data warehouse costs
Up to 80% cost savings for similar workloads
Cloud ≠ Modern
It started 40 years ago with the enterprise data warehouse
The cloud has not cured enterprise data warehouse shortcomings
Is the cloud data warehouse model...
From single source of truth to single point of access
Starburst simply accesses all data where it lives, regardless of location, and offers similar elastic scaling capabilities, fine-grained access control, client integrations, and performance of cloud data warehouses.
From data centralization & lock-In
to distributed data analytics
Starburst helps companies maximize value and recession-proof their data & analytics strategy by focusing their limited resources on the highest value activities for their business instead of managing their complex data environments
Starburst empowers its customers to
Have access to all data
Fast access to distributed data not only in CDW, but also federates to many other sources, with high concurrency
Purpose-built for data discovery, ad-hoc analytics, and long-running batch workloads
Work for today & tomorrow
Compute engine, allowing you to optimize your data storage
Use the SQL language your team knows with the tools they have
Consistent data access when migrating data to new storage
Optimize price / performance
Mitigate rising costs by offloading workloads to Starburst
Optionality in how and where queries are executed
Better control and automation over compute prioritization
Optionality
Leverage low cost object storage and open table formats of your choosing. Because Starburst doesn’t store your data, we give you control to optimize your infrastructure and efficiently use compute resources to decrease costs
Connectivity
ANSI-SQL engine allows users to use SQL as a conduit between BI and ETL tools, and any underlying data source. Access to over 50+ enterprise sources with Great Lakes connectivity that unifies open formats (Hive/Delta/Iceberg)
Data products
Bring analytics closer to the source for dramatic improvement in time-to-insight, with less infrastructure to manage. Curated, high quality datasets produced from multiple sources shortens the path from raw data to trusted insights
Any workload
In-memory execution enables rapid ad-hoc and interactive queries, while fault-tolerant execution ensures completion of long-running batch workloads and data transformations for efficient data pipelines
Significant Cost Savings
Starburst offers a host of benefits by enabling access to data where it resides. This approach leads customers to substantial cost savings and improved operational efficiencies. The first advantage is evident in lower infrastructure costs, as the data is accessed directly without the need for additional storage or processing layers. Moreover, Starburst provides easy and automated cluster management with auto scaling capabilities, streamlining the process and reducing the operational overhead significantly.
Another aspect that contributes to cost reduction is the ability to perform complex queries at a lower cost than traditional data warehouses (CDW). Starburst’s efficient querying mechanism ensures that customers can derive valuable insights without incurring excessive expenses. Additionally, the platform facilitates the analysis of streaming data without the need to copy or move it to a separate location. This eliminates data duplication and movement, further enhancing operational efficiency and reducing total cost of ownership (TCO).
Furthermore, Starburst empowers engineers by freeing them from the burdens of data movement and management. With the platform’s capabilities to access data in place and perform tasks seamlessly, engineers can focus on value-added projects that drive innovation and growth for their organizations. This holistic approach to data access and management enables businesses seeking to optimize their operations and maximize their resources effectively.
Customer Stories
“With Starburst, we could scale up and scale down as we needed, resulting in 30% fewer compute resources required.”
– Mike Prior, Principal IO Engineer, Optum
“Auto scaling with graceful shutdown was an attractive feature. We are now saving 50% on our AWS compute costs.”
– Alberto Miorin, Engineering Lead, Zalando
“Our core intention was to enable our end users to use the raw data we have in a much faster way, rather than waiting for developers or data engineers to provide it. That is how we decided on Starburst.”
– Sachin Menon, Sr. Director of Data, Priceline
“The amount of clickstream data would have been cost-prohibitive on Snowflake. An evaluation of Starburst and Snowflake, found that high complexity queries would have cost 4x as much to run on Snowflake compared to Starburst … Running large tables on Snowflake costs 500% more per year than running the same tables on Starburst. We tend to use Snowflake only for small tables vs our large tables where 500GB is queried per day using Starburst.”
– Director of Engineering, Online services marketplace
Learn More
Solution Brief
Extending your analytics with Starburst & Snowflake
Blog
The analytics engine for distributed data
Blog
The answer to the data warehouse hypocrisy
A single point of access to all your data
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