dbt (Data Build Tool) Support & Assessment
Last reviewed by Tyler Eastridge
AceMQ gives data teams independent production support, project assessment and upgrade planning for dbt (data build tool): dbt v1, dbt OSS and the full dbt v2 binary, running against your own warehouse or lakehouse. It covers slow builds, failing tests, CI that rebuilds everything and the move from v1 to v2, with a 15-minute emergency response. AceMQ does not write your models or build pipelines, and does not host dbt for other companies.
A senior engineer, not an SDR. No sales sequence attached.
Without hiring a data engineer or changing toolsFor production incident cover, see AceMQ dbt 24/7 support.
Customers
Partners
The Problem
Eight dbt problems that data teams bring to AceMQ, from a nightly build that now takes hours to test failures nobody reads and an upgrade blocked by package pins. If one describes your week, that is where the review starts.
dbt Core, dbt OSS, dbt and the dbt platform are used as if they were one product, and nobody can say which licence terms cover the team
The nightly build grew from minutes to hours and the only fix tried so far was a bigger warehouse
An incremental model has drifted from its source and a full refresh is the only known repair
Test failures are written to a log that nobody reads, so dashboards keep running on data that failed its checks
The project sits on a v1 minor whose support window is closing, and package and adapter pins block every upgrade
CI rebuilds the whole project for every pull request, so reviewers stop waiting for it
The analytics engineer who wrote the macros has left and nobody wants to change them
A job fails in the scheduler and the retry re-runs everything instead of the models that failed
A good fit if dbt already runs in production against a cloud warehouse or lakehouse and you want a written view of version, licence position, run cost and CI before the next upgrade.
Not a fit for small teams with non-critical workloads. AceMQ is not a budget consultancy: we work with enterprises running business-critical and compliance-heavy dbt.
How it breaks, and the fix
A dbt build runs models and their tests in dependency order and skips everything downstream of a failure. If the scheduler records the non-zero exit but alerts nobody, the tables behind the dashboard keep yesterday's rows, and the first sign is a report that looks right and is a day old.
One failed model, no alert
Sources, two models, tests and the dashboard tables
Both models build, their tests pass and the dashboard tables take the day's rows. Run time sits inside the window the business expects.
revenue_daily fails on a warehouse timeout. The build skips what depends on it and exits non-zero, but the scheduler only logs the exit code. The dashboard tables keep yesterday's rows and nobody is told.
The failure is routed to the model's owner, the build resumes from the point of failure instead of starting again, and the timeout is addressed by the model's materialisation and the warehouse size it runs on.
A build that fails quietly is one of the reasons teams call AceMQ about dbt. The fix is design: failure alerts routed to the model owner, test severity chosen so a warning does not page and an error does, source freshness checks that catch a feed that stopped arriving, retries that resume from the failed node, and incremental models with a defined repair path so a full refresh is not the only answer. AceMQ also checks that pull-request builds run only the models that changed.
Our Services
AceMQ runs five dbt (data build tool) service lines: a version and licence position, run performance and warehouse cost, v1 to v2 upgrade planning, an orchestration and CI review, and a fixed-scope project health check. Any of them can roll into 24/7 on-call with a 15-minute emergency SLA. AceMQ reviews and supports projects your team owns; it does not write models or build pipelines.
A written map of which dbt you run, which support window it is in and what dbt Labs publishes about the licence terms for your kind of use.
The models that cost the most time and warehouse spend, found from run artifacts and query history, with a tested change for each.
A plan to move a v1 project onto a supported release without a surprise: deprecations, packages, adapters and CI, with a rollback at each step.
How dbt is triggered, retried and tested: scheduler, pull-request builds and who is told when something fails.
The fixed-scope entry engagement: a written report on the state of the project that your own team can act on, with or without AceMQ afterwards.
Senior engineers on your account, a 15-minute emergency response, no ticket routing and no junior triage.
24/7 Support
AceMQ dbt support gives you an AceMQ engineer and a 15-minute first response when a production build is failing, 24/7. Lower severities get 1-hour, 4-hour and next-day responses. AceMQ supports your own deployment: it does not host dbt for other companies, and dbt Labs' platform support stays with dbt Labs.
P1 escalation path
A replay of one P1, from the first page to the written root-cause analysis
15-minute P1 response, 24/7.
A response time, not a resolution time.
P1 opened, on-call engineer paged
Phone, email or Slack reaches the on-call senior engineer directly, whether the incident is in RabbitMQ, Kafka, Redis, PostgreSQL or Kubernetes. No web form, no tier-1 queue.
Senior engineer on your bridge
A senior engineer who already knows your environment joins a live bridge, so nobody has to re-explain your topology.
Specialists across the stack join
When an incident crosses components, the engineers who know each one join. For RabbitMQ, the path runs to the core team.
Written root-cause analysis
Root cause, the fix applied and the prevention steps, delivered after every P1.
Beyond SLAs — the model behind senior-only, zero-cold-start expert access.
Tickets go to senior engineers briefed on your environment, not an anonymous queue. The proposal states who does the work.
Any ticket can be escalated to a live session with an engineer through calendar booking. No gatekeeping and no approval step.
Scheduled health checks on your deployment and alerts on risks in the versions you run, so problems surface before they reach production.
Proactive alerts on critical bugs and CVEs affecting your exact version, with version compliance monitoring so you're never caught off guard.
How It Works
An AceMQ dbt engagement runs in four stages: a scoping call with a quote within 1 hour, a read-only project review from your repository and run artifacts, written findings ranked by cost and risk, then a handover or ongoing cover. Nothing in production changes until you decide.
Quote within 1 hour
A senior AceMQ engineer asks how dbt runs today: which distribution and version, which warehouse or lakehouse, how many models and environments, where it is scheduled and who is on call. A quote request is answered within 1 hour.
Scoped per project
You share the repository and the run artifacts, such as manifest.json and run_results.json, and a view of warehouse spend by query. Nothing in production is changed and AceMQ needs no write access to your warehouse.
Scoped per project
A ranked report: slow and costly models, test and freshness gaps, CI and scheduling problems, the version and licence position, and an upgrade order with a rollback for each step.
Ongoing, if you want it
Your team works through the list, or AceMQ stays on call for the pipeline with a 15-minute P1 response and a written review after each incident.
A senior engineer, not an SDR. No sales sequence attached.
Typical engagements
Typical dbt engagements from AceMQ: what the project looks like, what AceMQ assesses or plans, and what the engagement delivers. Each card links to the full write-up.
Global Insurance Group
Resolving pipeline runtime blowouts caused by queries spilling to remote storage on undersized warehouses while concurrent jobs queued behind them.
Snowflake
dbt
Airflow
TerraformGlobal Logistics Provider
Restructuring warehouse sizing, auto-suspend policy, and workload isolation to bring credit consumption in line with the work actually being done.
SnowflakedbtTerraformAirflowFinancial Market Data Provider
Assessment of clustering keys, micro-partition pruning, and table design on large tables where queries had begun scanning most of the data.
SnowflakedbtAirflowTerraform
Retail Analytics Organization
Diagnosing an Airbyte connection that kept reporting success while the destination table quietly went stale after an upstream schema change.
Airbyte
PostgreSQLSnowflake
KubernetesdbtInsurance Services Group
A structured review of an Airbyte estate that had grown organically — auditing connector versions, sync modes, state handling, and failure visibility.
AirbyteKubernetesPostgreSQLdbt
Kafka
Healthcare Payer Organization
Planning and executing a staged move off Pentaho Data Integration onto a modern ELT stack, without a big-bang cutover of hundreds of transformations.
PentahoAirbytedbtPostgreSQLKubernetesSolutions
AceMQ covers dbt end to end. Projects: consulting and implementation, health checks and migrations. Ongoing cover in four tiers, from 24/7 support and incident management to proactive monitoring, managed dbt on your infrastructure and fully managed dbt on AceMQ infrastructure, plus end-of-life versions.
Projects
Fixed-scope work led by a senior engineer: architecture and new builds, a health check of what you run today, or a migration with a reversible cutover.
Support and managed services
Four tiers of ongoing cover once you are live. Each tier hands more of the day-to-day work to AceMQ, from a 15-minute emergency SLA to AceMQ hosting and running dbt for you.
Compare the four dbt support tiersSide by side
Since September 2026 dbt means four different things: v1, which keeps the dbt Core name, dbt OSS, the full dbt v2 binary and the hosted dbt platform. They differ in licence, in who ships fixes and in who may support them. The table sets out what dbt Labs publishes; your agreement with dbt Labs governs, and this is not legal advice.
| Question | dbt v1 (dbt Core) | dbt OSS (v2) | dbt (full v2 binary) | dbt platform |
|---|---|---|---|---|
| What licence applies? | Apache 2.0. | Apache 2.0. It is the open-source subset of v2, built from code dbt Labs relicensed from Elastic License v2 on 1 June 2026. | dbt Product Licensing Agreement: free to use internally, with terms for anyone who redistributes it as a managed service. | dbt Labs commercial terms of service, with a free tier within usage limits. |
| Where does it run? | On your laptop, CI runner or scheduler, against your warehouse. | The same places, as a compiled binary or from source. | The same places, with extra features such as SQL comprehension and the editor extension that work without a login. | Hosted by dbt Labs, with orchestration and other services. |
| What is the support window? | One year per minor. v1.12 is in active support to 15 July 2027 and v1.11 in critical support to 18 December 2026. v1.13 will be the last 1.x minor, with critical fixes expected for several years. | v2.0, released 14 September 2026, is in active support to 13 September 2027. | The same v2 release line and dates as dbt OSS. | Release tracks keep environments current. Versions v1.3 to v1.7 are removed on 31 January 2027. |
| Can an independent firm support it? | Yes. The code is Apache 2.0. | Yes. The code is Apache 2.0. | For your own deployment, yes: dbt Labs describes a consultant setting dbt up for a client's internal use as permitted. Hosting it for third parties triggers the redistribution terms. | Support runs through dbt Labs. AceMQ can review the project, CI and warehouse side but does not operate the platform. |
| When does it fit? | You are on v1 and a planned upgrade is not due yet. | Your policy requires an Apache 2.0 runtime. | You want the full v2 feature set and run dbt inside your own organisation. | You want dbt Labs to run scheduling and the editor for you. |
For the licence split and the support options in more detail, read dbt Core v1 vs dbt v2: licence and support options.
One partner, not five
dbt rarely fails in isolation. AceMQ covers the full surrounding infrastructure — so one team owns the whole path instead of pointing at each other.
Guides, articles and comparisons
Guides from AceMQ engineers on dbt licensing and support options, plus the AceMQ services around the data stack: Apache Airflow, Databricks and Snowflake.
FAQs
Five answers on dbt (data build tool) from AceMQ: what happened to the name dbt Core, who can support it, what AceMQ does not build, how long each version is supported and what an assessment covers.
Still have questions about dbt? Email an Expert
Yes. dbt Labs states that dbt v1.x remains Apache 2.0 and is still maintained. As of 4 November 2026 v1.12 is in active support until 15 July 2027, and v1.13, the last planned 1.x minor, is in beta with critical fixes expected for several years beyond the normal one-year window. The dbt Core name no longer applies to any v2 distribution.
For your own deployment, dbt Labs publishes that this is allowed: its redistribution terms bind those who provide dbt to third parties as a hosted or managed service, and its FAQ names a consultant setting up dbt for a client's internal use as permitted. AceMQ supports your deployment and does not host dbt for others. Read your own agreement and ask dbt Labs at license@dbtlabs.com if your case is unusual.
No. AceMQ assesses and supports projects that your team owns and plans their upgrades. Writing models, designing the warehouse schema and building ingestion pipelines are data engineering work that AceMQ does not offer.
AceMQ works with the warehouse side where it has its own coverage, such as Snowflake and Databricks, and with the schedulers around dbt, such as Apache Airflow. Scope is agreed in the scoping call, and a warehouse AceMQ does not cover is named as out of scope before a quote.
Yes. AceMQ works on dbt in two ways: ad hoc engagements for a defined piece of work, such as a health check, an upgrade or an incident, or an annual contract that covers 24/7 support and proactive reviews. Many teams start ad hoc and move to an annual contract once the first engagement is done.
Every AceMQ proposal is tailored to your requirements: your dbt environment, the SLA you need, the hours of cover and the scope of work. Most contracts run $24,000–72,000 a year, depending on the SLA, the scope and how dbt is deployed, with aggressive discounts when several technologies share one contract. Request a quote and AceMQ replies within 1 hour.
Let's talk
A senior AceMQ engineer reviews your dbt setup, tells you what cover fits and quotes it. Quote requests are answered within 1 hour.
Production incident right now?Email a dbt Architect
Send us a message and we'll follow up within 1 hour — or book a free 30-min consultation directly.
305-204-2607info@acemq.comPrefer to talk now? Call us directly or use the consultation tab to find a time that works.
