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Databricks Lakehouse (Databricks SQL)
Your engineers work in the lake, your analysts in a warehouse. The same table now exists twice — Databricks Lakehouse — still Databricks SQL on the bill — runs SQL warehouses over open Delta Lake and Iceberg tables governed by Unity Catalog, on AWS, Azure or Google Cloud, with serverless SQL in Mumbai and Pune at published per-DBU rates.
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How it’s rated
Full scoreboard ↓Quick answer
The Databricks platform family
This page covers Databricks Lakehouse (Databricks SQL) — with AI/BI dashboards, Lakehouse//RT and Lakehouse Federation folded in. The rest:
Quick facts
30-second orientation- Product
- SQL warehousing on the lakehouse: Serverless, Pro and Classic warehouses over Delta Lake and Apache Iceberg tables
- Maker
- Databricks, Inc., San Francisco; founded 2013 by the creators of Apache Spark; valued at $190B in August 2026
- Name
- Marketed as Lakehouse, “its data warehousing product”; the docs, SKUs and invoices still read Databricks SQL
- Price
- SQL Serverless $0.70 per DBU in US East, $0.77 in AWS Mumbai and Azure Central India; Pro $0.55; Classic $0.22
- Compute
- Serverless includes the cloud instances; Pro and Classic run in your own cloud account and add its VM bill
- BI
- AI/BI dashboards and Genie carry no extra licence fee; they run on the same SQL warehouse DBUs
- Deployment
- AWS, Microsoft Azure or Google Cloud, billed per second; there is no on-premises or self-managed edition
- Proof
- Databricks says Lakehouse passed a $1.5B revenue run-rate in August 2026, growing more than 100% a year
- India
- Serverless SQL in AWS Mumbai, Azure Central India (Pune) and GCP Mumbai, about 10% above US East rates
- In India via
- TechBag — warehouse sizing, committed-use terms and the quote itemised in INR with GST
Understand the lakehouse warehouse before you buy it
Most product pages skip this. We start here — so you buy a capability, not a buzzword.
What is Databricks Lakehouse?
It is the SQL warehouse of the Databricks platform, still billed as Databricks SQL, querying open tables in your cloud.
A separate warehouse beside the lake vs Databricks Lakehouse — the honest table
What consolidation actually replaces, dimension by dimension.
| Dimension | A separate warehouse beside the lake | Databricks Lakehouse (Databricks SQL) |
|---|---|---|
| Copies of data | A warehouse copy beside the lake | One open-format copy for SQL, Spark and AI |
| Compute | Clusters sized and started by hand | Serverless warehouses billed per second |
| Governance | Grants per tool, lineage on a wiki | Unity Catalog grants, masks and lineage |
| Dashboards | A separate BI licence per viewer | AI/BI dashboards on warehouse DBUs, no licence |
| Other databases | Nightly copy jobs into the warehouse | Lakehouse Federation queries them in place |
| What it is NOT | — | An on-premises appliance, or a flat monthly price |
The cheapest test is one dashboard on a serverless warehouse for two weeks: read the DBU usage before you size any commitment.
The four pieces of the platform
Vendors love diagrams; buyers need to know what they’re actually operating. Here’s the whole platform, demystified.
Storage
Tables are open-format files in cloud object storage: Databricks default storage at $0.023 per GB-month in US East and $0.025 in Mumbai, or your own bucket.
Catalog
Unity Catalog holds permissions, lineage and the audit trail for each table and view, so one grant covers SQL, notebooks, dashboards and Genie.
Warehouses
SQL warehouses run the Photon engine. Serverless lives in Databricks’ compute plane in your region; Pro and Classic start on VMs in your own account.
Consumers
The SQL editor, AI/BI dashboards, Genie and outside tools such as Power BI and Tableau all send their queries to one warehouse and its DBU meter.
Open tables in object storage, Unity Catalog on top, SQL warehouses running the queries — serverless in Databricks’ plane, Pro and Classic in your own cloud account.
Nine capabilities. Govern, query, serve.
Databricks Lakehouse puts a SQL warehouse on the same open, governed tables your engineers and data scientists already use.
Open tables, one copy
Delta Lake and Apache Iceberg tables in object storage, read by SQL, Spark and outside engines with no second proprietary copy.
Unity Catalog permissions
Grants, row filters, column masks and lineage are set once in Unity Catalog and apply to every warehouse query and dashboard.
Other databases, in place
Lakehouse Federation queries tables in other systems where they sit, under the same Unity Catalog rules, before any copy is made.
A vectorised query engine
Photon, Databricks’ massively parallel engine, runs warehouse SQL; Databricks says its queries are 5x faster than three years ago.
Warehouses with no cluster
Serverless warehouses fold the cloud instances into the DBU price and bill per second after one minute, Indian regions included.
Materialized views, streaming
Materialized views and streaming tables keep SQL results current, with AUTO CDC generally available since June 2026 for changes.
Dashboards and Genie
AI/BI dashboards and Genie plain-language questions run on the warehouse with no licence fee; the DBUs they use are still billed.
Lakehouse//RT, in Beta
A serverless warehouse type for sub-second reads at high concurrency, in Beta since 30 June 2026 and 30% off until 31 January 2027.
Power BI, Tableau, metrics
Power BI and Tableau connect directly, and metric views define each business measure once so every tool reports the same figure.
Watch Databricks explain its Lakehouse warehouse
Three videos from Databricks’ official channel: Reynold Xin’s June 2026 talk on Lakehouse//RT, a December 2025 AI/BI dashboards demo and a January 2025 explainer on serverless SQL warehouses.
Lakehouse//RT, the real-time Lakehouse powered by Reyden — Reynold Xin, Co–founder & Chief Architect
A 14-minute talk from June 2026 in which co-founder Reynold Xin introduces Lakehouse//RT, now in Beta, and the Reyden engine.
Interactive Storytelling and Reporting with AI/BI Dashboards
An 8:35 demo from December 2025 of building AI/BI dashboards that tell a story, served from the same SQL warehouse.
Databricks Serverless SQL Warehouses
A 3:30 explainer from January 2025 on what serverless SQL warehouses are and what Databricks runs on your behalf.
Want a live, India-context walkthrough for your environment?
Book a guided demo →Most estates pay to keep the lake and the warehouse in step. Databricks Lakehouse queries the one copy.
Here’s what genuinely sets it apart — and exactly where it stops.
One governed copy for SQL, engineering and AI
Warehouse tables are open Delta Lake or Iceberg files under Unity Catalog, so the SQL analysts, the Spark engineers and the AI work all read one governed copy, and Lakehouse Federation reaches other databases in place. Gartner named Databricks a Leader in its 2025 Cloud DBMS Magic Quadrant, a fifth year running.
Published rates, cloud by cloud and region by region
Databricks prints its $/DBU for every tier, cloud and region: SQL Serverless $0.70 in US East and $0.77 in AWS Mumbai and Azure Central India, Pro $0.55, Classic $0.22. Billing is per second, so a stopped warehouse costs nothing, and committed-use discounts can be spent across clouds.
Dashboards and plain-language questions with no licence
AI/BI dashboards and Genie come with the warehouse: Databricks charges no extra licence, only the DBUs the queries use. Power BI and Tableau connect as well, and metric views pin each measure down once. Lakehouse//RT, still in Beta, adds a warehouse type for sub-second reads at high concurrency.
Where it stops
Classic and Pro warehouses add your own cloud VM bill and take 4–6 minutes to start; serverless has a one-minute minimum and costs about 10% more in India. Lakehouse//RT is Beta with no SLA. There is no on-premises edition and no INR price list, and DBU use is hard to forecast without test runs.
The numbers behind the platform
What your Databricks Lakehouse rollout looks like
List the workloads
List the reports, marts and BI tools to move, and note which already read Databricks tables and which sit elsewhere.
Pick the warehouse type
Start a serverless SQL warehouse in Mumbai or Central India, set budgets and put Unity Catalog grants in place.
Run representative queries
Replay real dashboards and SQL for a few weeks and read DBU use per warehouse, as Databricks itself advises.
Move BI and dashboards
Point Power BI or Tableau at the warehouse, rebuild key boards in AI/BI where it helps, and define metric views.
Commit and quote
Size a committed-use deal from the measured DBUs and get TechBag’s quote itemised in INR with GST before signing.
The review scoreboard
Modelled on Gartner Peer Insights structure. *Counts and breakdowns are illustrative pending verified review collection.
Quick poll — what’s driving your evaluation?
Talk to an advisor“Moving our reporting marts onto serverless warehouses in Mumbai ended the weekend cluster babysitting our team used to do.”
“One Unity Catalog grant now covers analysts in SQL and data scientists in notebooks, which our auditors were glad to see.”
“AI/BI dashboards replaced a separate BI licence for plant managers; warehouse DBUs rose, but the total bill went down.”
“Classic looked cheapest per DBU until we added the EC2 bill and the start-up wait. We moved most work to serverless.”
“Forecasting DBUs took two months of test runs, and the Mumbai serverless premium surprised finance. Set budgets early.”
“Power BI on the warehouse works well, and metric views stopped three teams reporting three different revenue numbers.”
Where everyone sits — the grids
Analyst firms bury this view behind paywalls, and review-site grids score satisfaction, not fit for your estate. So here’s TechBag’s synthesis of the cloud data warehouse and lakehouse market — tap any vendor to see why it sits where it does.
TechBag Cloud Warehouse Grid
Execution strength vs product vision — the classic market map, minus the paywall.
Gartner Cloud DBMS Leader 2025; serverless SQL from $0.70 a DBU.
Openness × Workload Breadth
The grid nobody publishes — how open and portable the data is vs how many workloads run on the one copy: SQL, engineering, machine learning, BI and AI.
Open Delta and Iceberg on three clouds; SQL, Spark, ML and AI/BI on one copy.
Positions are TechBag’s illustrative synthesis of public review-platform data and vendor documentation — not a reproduction of any analyst graphic. Verify before relying on it.
Databricks Lakehouse vs the cloud warehouse field
Against Snowflake AI Data Cloud, Google BigQuery, Microsoft Fabric, Amazon Redshift and SAP Business Data Cloud — on compute, billing, AI and BI, storage, price and India regions.
| Dimension | Databricks Lakehouse (Databricks SQL) | Snowflake AI Data Cloud | Google BigQuery | Microsoft Fabric | Amazon Redshift | SAP Business Data Cloud |
|---|---|---|---|---|---|---|
| What it is | Lakehouse SQL warehouse | Credit-billed platform | Serverless SQL analytics | Capacity-billed SaaS | AWS-native warehouse | SAP data and analytics |
| Deployment | AWS, Azure or GCP | Any of three clouds | Google Cloud only | Azure only | AWS only | Run by SAP |
| Compute choices | Serverless, Pro, Classic | Sized warehouses | Nothing to size | One shared F-SKU | 4–1,024 RPU base | No published unit |
| Billing granularity | Per-second billing | Per second, 60 s first | By bytes scanned | CU-hours while running | Per second, 60 s first | Subscription term |
| AI and BI on top | AI/BI and Genie, no fee | Cortex on AI credits | Vertex AI and Gemini | Power BI and Copilot | Redshift ML | Joule on SAP data |
| Storage price | $0.023 per GB-month | $23 per TB-month | From $0.02 per GiB | $0.025 per GB-month | $0.024 per GB-month | Not published |
| Free trial or tier | Trial and Free Edition | Credits on sign-up | 1 TiB a month free | 60-day trial capacity | $300 credit, 90 days | None documented |
| Pricing model | DBUs by SKU and region | Credits by edition | On-demand or editions | CU-hours, reservable | RPU-hours or nodes | Quote per customer |
| Published entry price | $0.70 per DBU | $2 per credit | $6.25 per TiB | F2 ~$262 a month | $0.375 per RPU-hour | Not published |
| Integrations | Federation, OpenSharing | Marketplace, Openflow | Read in place | OneLake for Power BI | Zero-ETL feeds | SAP sources first |
| India data region | Mumbai, Pune, GCP Mumbai | Mumbai and Pune | Mumbai and Delhi | Central India | Mumbai and Hyderabad | Not published |
| Lock-in and exit | Open formats, any cloud | Snowflake-run storage | Tied to Google Cloud | Azure and Power BI pull | AWS-bound | SAP-shaped layer |
| Support and buying | Card or commitment | On demand or prepaid | On the GCP bill | On the Azure invoice | Paid support for tech | SAP contract |
| Best fit | Lakehouse-first teams | Fully managed analytics | Google Cloud estates | Microsoft 365 shops | AWS database estates | SAP-centred firms |
Which approach fits you?
Honest fit signals — because the fastest way to lose your trust is to pretend one product wins every scenario.
Choose Databricks Lakehouse (Databricks SQL) if…
- ✓Your data engineering and ML already run on Databricks and you want SQL analytics on the same governed tables
- ✓You want published $/DBU rates and serverless SQL in AWS Mumbai, Azure Central India or GCP Mumbai
- ✓Open Delta Lake or Iceberg files matter more to you than a single all-in price
Compare alternatives if…
- ✓You want a service with no cloud account of your own to run — Snowflake prices Mumbai and Pune at US East rates
- ✓Your estate is Microsoft 365 and Power BI — Fabric bills one capacity for all of it
- ✓You want pay-per-query pricing and no warehouse at all — BigQuery charges $6.25 per TiB
Do not expect…
- ✓An on-premises edition or an INR price list
- ✓A flat, predictable bill — DBUs follow usage, and Classic adds your cloud VM bill
- ✓Production SLAs on Lakehouse//RT — it is still in Beta
Databricks Lakehouse (Databricks SQL) is one of 28 databases & data tools products TechBag carries. The Databases & Data Tools guide narrows them to a shortlist and shows the reasoning. →
What does keeping a separate warehouse in step cost you?
Drag the sliders (data pipelines feeding a separate warehouse; engineer-hour cost). Estimates model the engineering time spent copying data from the lake into a warehouse, reconciling the two copies and managing access twice, at an assumed 1.5 hours per pipeline a month, with 70% of it removed by querying one governed copy. Both figures are assumptions. Illustrative.
Loaded cost = salary + overheads per productive hour. Illustrative only — your TechBag quote models your actual environment and modules.
Three ways to consume it
Published list prices, USD, pay-as-you-go, as of October 2026. SQL Serverless is $0.70 per DBU in US East and $0.77 in AWS Mumbai, Azure Central India and GCP Mumbai, with the cloud instances included. SQL Pro is $0.55 ($0.61 in India) and SQL Classic $0.22 everywhere, and both add the VM bill your own cloud account pays. Billing is per second with a one-minute minimum; default storage is $0.023 per GB-month in US East and $0.025 in Mumbai. Committed-use contracts discount these rates. TechBag quotes in INR with GST.
SQL Serverless
Best for most new warehouse workloads
- $0.70/DBU US East, $0.77 Mumbai and Pune
- Cloud instances included in the rate
- Per second after a one-minute minimum
+ Platform add-ons
Best for a broader rollout
- Scoped to your estate
- Add-on modules as needed
- Phased, right-sized deployment
SQL Pro and Classic
Best where you must run compute in your own account
- Pro $0.55/DBU, Classic $0.22/DBU
- Plus the VM bill from your cloud
- 4–6 minute start-up per warehouse
Buy it for less — TechBag pricing beats list
Whatever the list prices above, TechBag negotiates a significantly better deal — with GST-compliant INR invoicing and local support. Ask us for your discounted quote.
Get an India-ready quote
Tell us your requirements and current tools — we’ll model it against what you spend today.
The 8 questions to ask every vendor
Take this into your next vendor call — including ours.
Which workloads need Serverless, and which could run on Classic or Pro once the VM bill is added back?
Will the workspace sit in AWS Mumbai, Azure Central India or GCP Mumbai, and is the ~10% premium budgeted?
How many DBUs a day did representative test runs use, and what is that at $0.77 in your region?
What discount does a committed-use deal give, and can unused commitment move across clouds or products?
Premium or Enterprise? On Azure, Premium matches the Enterprise tier on AWS and GCP; Standard is retired.
If Lakehouse//RT is in scope, what are its price and support once Beta and the January 2027 offer end?
Will tables sit in Databricks default storage at $0.025 per GB-month in Mumbai, or in your own bucket?
What term, tier and commitment does the quote cover? Ask TechBag for it in INR with GST, storage itemised.
Questions buyers ask
Ready to evaluate Databricks Lakehouse?
List the reports and marts you want to move, or let a TechBag advisor size Serverless against Classic, check the Mumbai and Pune rates and get a committed-use quote itemised in INR.
Stats, ratings, review counts and pricing are illustrative and sourced from public materials; verify before purchase.