The AI-first data stack
dbt Cloud alternative
Transform your data into datasets with our AI Copilot
Use our AI Copilot to transform raw data into analytics-ready datasets.
Tableau alternative
Give everyone a governed, AI-powered BI tool
Enable business users to explore data on their own, with text-to-sql.
Connect your data
Buster seamlessly integrates with whatever data stack you currently have. We connect to all major databases & data warehouses.
One-click deploy a blazing-fast data warehouse
Our headless data warehouse is built on StarRocks, Apache Iceberg, & object storage. It’s really, really fast & extremely cost-effective.
(you can also query your own database/warehouse directly, it's totally up to you)
Sub-200ms response times
StarRocks excels in performance benchmarks. The normal query time in StarRocks is under 200ms. It's serverless and purpose-built for real-time analytics at scale.
Built to perform at massive scale
Over the past 3 years, companies like Apple, Airbnb, Stripe & more have migrated their analytics to Apache Iceberg. It’s faster, more cost-effective, and scales better than traditional warehouses structures.
90% cheaper than alternatives
Rapidly build datasets, with help from AI
Use our AI copilot to rapidly create LLM-ready datasets. Our AI copilot is context-aware of your data structures and can help you build robust datasets in minutes. You can also use existing models or views in dbt, LookML, Cube, etc.
Enable anyone to explore data with natural language
Enable business users to query data on their own, using plain english. Business users can build dashboards, schedule reports, and more - with a modern, friendly UX.
Analytics that don’t break
Keep your data clean, reliable & optimized
Auto-generate documentation, manage versions in Git, merge LLM-suggested fixes, seamlessly sync with dbt & more.
Version control & Git
All of your metadata, datasets, and more live in Git. This makes it easy to version control your documentation, datasets, and more. You can even sync Buster with existing repos.
Dependency management
Buster automatically tracks dependencies between your schema, datasets & dashboards. Whenever there is a breaking change, Buster uses LLMs to fix impacted dependencies throughout your stack.
Seamlessly integrate with dbt
Buster automatically syncs model and metadata changes from dbt with your datasets & documentation in Buster. You can also push datasets created in Buster to DBT, creating a new pull request in your git repo.
Inbox
AI-suggested edits & fixes
Buster automatically detects missing documentation & dataset improvements - then creates a proposed edit. Proposed edits can be discarded, altered, or approved by you.
Average Confidence Score
Last 30 days
94.5%
Low confidence queries (9)
Name
Nate Kelley
Blake Rouse
Gregory
Dallin Bentley
Another name
Another name
Another name
User
Aaron Epstein
Nicolas Dessaigne
Brad Flora
David Lieb
Gustaf Alstromer
Tom Bloomfield
Paul Graham
Dataset
Revenue & Sales Rep Perf
Product, Usage & Revenue
Support & Customer Info
Product, Usage & Revenue
Product, Usage & Revenue
Revenue & Sales Rep Perf
Various Items
Question
which customers buy th emost
show me my sales broken down by product category by month for the last 12
Who are our top customers.
Who are our top customers.
Various Items
Various Items
Various Items
SQL
WITH recent_sales AS (
WITH monthly_sales AS (
SELECT * FROM orders
SELECT * FROM orders
Various Items
Various Items
Various Items
Notes
Uncertain if orders can
Unable to id
Uncertain if orders can
Uncertain if orders can
Various Items
Various Items
Various Items
Evaluate text-to-SQL performance
Get full visibility into how your text-to-SQL is performing. Automatically detect low-confidence SQL queries, document fixes, and improve accuracy over time.
Open source, free to use
Bring your own storage
Intelligent caching
Query safety and permissioning
Secure credentials storage
SOC 2, HIPAA, & GDPR