Databricks vs. Starburst
A real open data lakehouse lets you pick your open formats. Works with your data in and around the data lake, on-premises and in the cloud. Is easy to use.
50-75%
faster time to insight realized at a multi-national bank
#1
Quality of Support and Product Direction in G2’s Grid Report
Starburst is a Leader in Big Data Processing and Distribution
Don’t take our word for it. Starburst is named #1 for Quality of Support and Ease of Use in G2 Crowd’s Grid Report based on real customer reviews. Additionally, customers said Starburst beat out Databricks in all of these categories:
- Quality of Support
- Ease of Admin
- Ease of Use
- Meets Requirements
- Breadth of Partner Applications
- Product Direction
- Data Visualization
- Performance and Reliability
Databricks Comparison Factors to Consider
When looking for a data lakehouse solution, you should look for one that lets you pick your open formats, easily works with your data in and around the data lake, and is a hybrid solution, supporting on-premises and in the cloud data storage.
Simplicity
A simple and intuitive experience includes everything from simple pricing models, ease of governance and management, minimal overhead and time to get started, a simplified customization and configuration experience, and most importantly just easy to use by any SQL user — a PhD should be optional.
Access
Empower data teams with the ability to securely use all their data assets, no matter where they live, across data lakes, data warehouses, and databases. With your modern data lake analytics platform easily discover, create, govern, share, and collaborate on curated data sets by connecting your data silos before, during, and after your modernization journey.
Scalability
A modern data lake analytics platform with high concurrency puts the control in your hands to ensure performant scalability is available when you need it most while optimizing price-to-performance for all analytics workloads.
Optionality
A modern data lake analytics platform takes the lakehouse architecture beyond the basics of open file and table formats by providing choice in hybrid or cloud environments, more data federation, seamless cross-cloud and cross-region analytics, choice in data catalogs without compromising the user experience and offering an enhanced MPP SQL query engine based on open standards and supported by the largest internet companies in the world.
Simplicity
A simple and intuitive experience includes everything from simple pricing models, ease of governance and management, minimal overhead and time to get started, a simplified customization and configuration experience, and most importantly just easy to use by any SQL user — a PhD should be optional.
Built-in data security
Automated cluster management
Built-in real-time usage monitoring
GenAI text-to-SQL
Automated data lake optimization
24x7 Customer support
Automated data maintenance
Get started within 10 minutes from first sign-on
Simple and transparent pricing and costs
Comparison based on publicly available information as of July 1, 2024
*In preview. Contact us to learn more.
Access
Empower data teams with the ability to securely use all their data assets, no matter where they live, across data lakes, data warehouses, and databases. With your modern data lake analytics platform easily discover, create, govern, share, and collaborate on curated data sets by connecting your data silos before, during, and after your modernization journey.
Universal search
Schema discovery
Data lineage
Dynamic Data Masking: Row filters and Column masks
Automatic end-to-end encryption
Time-based access control policies
Metadata tagging
Private link for AWS, Azure, and Google
Automatic data classification
Data profiling
Data obersability
Universal sharing
RBAC
Dynamic Catalogs
ABAC
Streaming ingest into Iceberg Tables
Integration with AWS LakeFormation
Supports 20+ popular data sources for federation
Supports hybrid data architectures
Optimized connectors for data federation
First-class support for multiple data catalogs
Federated data products
Data product sharing
Comparison based on publicly available information as of July 1, 2023
*In preview. Contact us to learn more.
Scalability
A modern data lake analytics platform with high concurrency puts the control in your hands to ensure performant scalability is available when you need it most while optimizing price-to-performance for all analytics workloads.
High concurrency
Fault tolerant execution (FTE)
Ad-hoc and interactive queries
Materialized views
Autoscaling by adding/removing incremental nodes
Customizable scaling for cost and performance optimization
Smart caching
Results and repeated subquery caching
Smart indexing
Index and cache resilience
Comparison based on publicly available information as of July 1, 2023
*In preview. Contact us to learn more.
Optionality
A modern data lake analytics platform takes the lakehouse architecture beyond the basics of open file and table formats by providing choice in hybrid or cloud environments, more data federation, seamless cross-cloud and cross-region analytics, choice in data catalogs without compromising the user experience and offering an enhanced MPP SQL query engine based on open standards and supported by the largest internet companies in the world.
Runs on multiple clouds
Supports popular open file formats
Standard ASNI SQL
Supports Python
Dataframe API for Python
OS MPP SQL query engine
First-class data federation with first and third-party data catalogs
Natively run SQL on Iceberg, Delta Lake, Hudi, and Hive table formats
Built-in cross-cloud and cross-region querying
Supports hybrid cloud architecture
Supports Apache Ranger
Comparison based on publicly available information as of July 1, 2024
*In preview. Contact us to learn more.
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