Databricks
Lakehouse to live application.
TechFabric is a Databricks partner with 80 Databricks-certified engineers, and Databricks is where we have chosen to go deep. We build data platforms, governed AI systems, and native Databricks applications on Unity Catalog, Lakeflow, Databricks Apps, AI Gateway, and Genie. We run our own business on the same stack, and the accelerators underneath it are free and open source.
80
Databricks-certified engineers on the bench today. That is the count as it stands. Certification proves the floor. Fifteen years of average production experience is what decides whether the thing still works in month six.
- 27
- source platforms with migration playbooks that execute, from Snowflake and Synapse to Teradata and SAP
- 4
- engagements with a fixed shape and a fixed fee, so you know the cost before the first meeting
- 10 to 3
- the delivery team size Fabric took us to, on the same Databricks stack we build yours on
Four ways to start, each with a fixed shape.
Each one has a length, a price and a written deliverable agreed before it starts. You get to judge how we work on something small enough to walk away from.
Two weeks
Health Check
Teams already on Databricks whose bill is growing faster than the work
Two weeks
Migration Readiness Sprint
Teams with a migration approved and a scope nobody can defend yet
Six weeks
Lakehouse Launchpad
Teams modernising off a legacy warehouse, or stalled after a pilot
Two to four weeks
Genie Accuracy
Teams whose natural-language analytics lost the room
If you already know the source.
These pages say what breaks on that platform, and what a person still has to do after Lakebridge has run. The first two weeks are the same sprint either way.
Snowflake
Snowflake to Databricks
Teams leaving Snowflake whose scope is still a table count
Azure Synapse
Synapse to Databricks
Teams leaving Azure Synapse whose dedicated pool, Spark and ADF still live as three projects
Teradata
Teradata to Databricks
Teams leaving Teradata whose load jobs and macros are still the system of record
Airlift carries executable playbooks for twenty-seven source platforms. Redshift, Oracle, SQL Server, BigQuery, Netezza, Greenplum, Vertica, Hadoop, SAP and Db2, along with the pipeline tools around them and the streams that move with the estate. The full registry is at airlift.fabric.pro/docs/sources.
Accelerators doing the heavy lifting.
We run all of this software ourselves. Every Databricks programme repeats the same few problems, and these are what we stopped rebuilding: the migration, the agent runtime, the evaluation harness.
A governed migration factory for moving warehouse and ETL estates to Databricks.
A governed delivery accelerator for Databricks Apps and GenAI workloads.
Governed mission control for running data and ML workloads on Databricks.
A Databricks adoption accelerator for quality engineering, experimentation, and governed delivery.
FAQ
Questions we get asked about Databricks
We are already on Databricks and shipping is the hard part. Where do you fit?
That is the engagement we are sharpest for. Usually it is the initiative that keeps slipping because your team is fully committed elsewhere: the app that never leaves the notebook, the agent nobody trusts in production, the Lakebase service that keeps getting deferred. We take ownership of that piece without pulling anyone off the current roadmap, and we work in your workspace so nothing has to be handed back later.
What makes you different from a data consultancy?
We are a software company that went deep on Databricks rather than a data practice that added application work later. Most partners stop at the pipeline and the dashboard. We build what comes after: the application on top, the durable API underneath, the agent that survives production. That is ordinary work here.
How many Databricks-certified engineers does TechFabric have?
Eighty, as things stand today, sitting inside a team of 115+ across Phoenix, Amsterdam, Dnipro and Hyderabad. Certification only proves the floor. What matters more is that the same engineers have shipped production software for fifteen years on average.
Do we have to already be on Databricks to work with you?
No. Some engagements start before the first workspace exists, some rescue a stalled pilot, and some are a migration off a warehouse that has stopped paying for itself. Databricks is where we go deepest and it is what we lead with, and it is not a condition of working with us. We also build on Azure, AWS, GCP and Cloudflare.
Which Databricks surfaces do you work with?
Unity Catalog, Lakeflow, Delta, Databricks SQL, Databricks Apps, Model Serving, AI Gateway, Genie, Lakebase and Asset Bundles. Our accelerators are built on those same surfaces, so what we recommend is what we run.
Tell us what is stuck.
A technical conversation with a senior engineer. If a two-week health check is the honest answer, we will say so.