# Linear Connector: integrate with BigQuery, Redshift, ClickHouse, and more without manual pipelines

> Managed connector to sync Linear issues, cycles, and projects to BigQuery, Redshift, ClickHouse, and more. Incremental, no-code.

Source: https://www.erathos.com/en/blog/new-linear-connector
Em português: https://www.erathos.com/blog/new-linear-connector
Published: 2026-08-11
Category: New Connectors

![Linear logo with an arrow pointing to the data warehouse, representing project data synchronization](https://cms-media.erathos.com/Zj8EigMdk52Zy53CW9TMZJobwT8-1.png)

Engineering teams live in Linear. Issues created, cycles closed, projects delivered, and within all this activity lies a massive volume of data about how your team actually functions: cycle time, backlog health, throughput, resolution rate. The problem is that this data has always been trapped inside Linear, disconnected from the rest of your analytical stack.

The Linear API is well-documented and uses GraphQL, which makes it seem simple to pull issues and cycles directly to your warehouse with a custom query. In practice, this turns into a script that someone has to maintain forever, dealing with cursor-based pagination, GraphQL API query complexity limits, and schema evolution as Linear adds new fields to objects. The Erathos connector delivers this integration as a managed service, without requiring your team to write or maintain this code.

## The problem with custom-built Linear pipelines

Most ingestion tools treat connectors as a black box: you point to an API, data is pulled, and you pray that it works. When something breaks, you find out weeks later, downstream, in a broken dashboard.

**Cursor-based pagination and query complexity limits.** Linear's GraphQL API uses cursor pagination and limits the complexity of each query. A naive extraction trying to pull issues with all related fields (labels, comments, state history) in a single query hits this limit, and the logic to break this down into smaller queries must be written and maintained.

**Unannounced schema evolution.** Linear frequently adds new fields to objects like issues and cycles. Without an automatic schema evolution strategy, every single change requires manual updates to the pipeline before the new data can start flowing.

**Forgotten token rotation.** Linear authentication uses a Personal API Key generated within the workspace. A simple script usually hardcodes this token or stores it in an environment variable without any rotation process. When someone accidentally revokes the key (or it is regenerated for security reasons), the pipeline silently stops until someone notices the missing data.

**Non-existent observability.** Without row counts per run, comparison with the previous window, or volume drop alerts, you are flying blind. A pipeline that ran successfully might have pulled zero new issues because the cursor got stuck.

## What you can ingest

The Linear connector delivers eight endpoints ready to be materialized in your destination data warehouse:

Endpoint

What it contains

`issues`

Issues with workflow states, priorities, labels, assignees, and cycle times

`teams`

Teams, organizational structure, and settings

`users`

Users, for attribution and workload analysis

`projects`

Projects linked to teams, milestones, and status updates

`workflow_states`

Workflow states, for process compliance tracking

`cycles`

Sprint data, including scope, velocity, and completion rates

`issue_labels`

Labels applied to issues

`comments`

Comments, for communication pattern analysis

Supported destinations are **BigQuery**, **Redshift**, **Databricks**, **ClickHouse**, **PostgreSQL**, **Supabase**, **Azure Synapse**, and **Amazon S3**.

## What you can do once Linear data hits your warehouse

**Engineering performance analytics.** Combine Linear cycle data with your deployment logs to build real, contextualized DORA metrics. It is the same kind of analysis we detailed in the [GitHub connector post](/blog/conector-github-lancamento), and it becomes even more robust when you cross-reference planning data (Linear) with execution data (GitHub).

**Backlog health monitoring.** Track issue aging, triage latency, and label distribution over time in your warehouse, with a level of granularity that no native Linear report can provide.

**Cross-functional reporting.** Cross-reference Linear project data with your CRM, support tickets, or product usage data to understand how engineering effort translates into customer value.

**Data-driven sprint retrospectives.** Stop reconstructing what happened from memory. Query historical cycles directly, organized in progressive quality layers as proposed by the [Medallion Architecture](/blog/arquitetura-medalhao-guiacompleto).

## Why outsource ingestion to Erathos

The premise of the connector is straightforward: maintaining ingestion pipelines shouldn't be your data team's responsibility. Pagination, query complexity limits, OAuth renewal, schema evolution, failure alerts, volume drop alerts, backfills. All of this is the responsibility of the ingestion platform operator.

With the connector configured, the platform delivers:

**End-to-end visibility of every execution.** You see exactly which records were fetched, which were skipped, and why. When a metric changes on your dashboard, you have the full audit trail to find the root cause.

**Total control without code.** You control the sync frequency, the incremental cursor, and how schema changes are handled, without writing a single line of infrastructure code.

**Reprocessing as a standard operation.** When you need to reprocess a window, either because your model logic changed or because you received a correction from the source, it is a platform operation, not a makeshift script.

[Brick, a Curitiba-based insurtech that centralized their data ingestion with Erathos](/clientes/brick-software), has Linear as one of the connected sources in their stack today, alongside HubSpot, Conta Azul, and GitHub, all maintained by a single data analyst, without a dedicated data engineering team for pipelines.

## How to authenticate

Connector authentication requires one field:

- **Token**: your Linear Personal API Key

To generate the token, navigate in Linear to **Settings > API > Personal API keys**, click **Create key**, give it a name, and copy the generated value. Paste it into the **Token** field in Erathos.

The complete process is documented at [docs.erathos.com/connectors/apis/linear](https://docs.erathos.com/connectors/apis/linear). Once connected, you select which teams and object types to sync, define the target schema, and Erathos handles the rest.

## Frequently asked questions about the Linear connector

**Does the Linear connector use an API key or OAuth?** Personal API Key. You generate the token under Settings > API > Personal API keys within your Linear workspace and paste it into the Token field in Erathos when configuring the connection.

**Does the connector sync more than one Linear team?** Yes. Once connected, you choose which teams and which object types (issues, cycles, projects, etc.) to sync, without having to configure a separate connection per team.

**Does the connector support incremental sync?** Yes, all objects, including issues, cycles, and comments, are synced incrementally after the initial historical load.

**Does Linear's GraphQL API query complexity limit affect the sync?** Not on your end. The connector already handles this by splitting extractions into queries that fit within the complexity limits allowed by the API.

**Which destinations can the Linear connector sync data to?** BigQuery, Redshift, Databricks, ClickHouse, PostgreSQL, Supabase, Azure Synapse, and Amazon S3.

## Available pipelines

The Linear connector is available with the following destinations:

- [Linear → BigQuery](/pipelines/linear-bigquery)
- [Linear → Redshift](/pipelines/linear-redshift)
- [Linear → Databricks](/pipelines/linear-databricks)
- [Linear → ClickHouse](https://www.erathos.com/pipelines/linear-clickhouse)
- [Linear → PostgreSQL](/pipelines/linear-postgresql)
- [Linear → Supabase](/pipelines/linear-supabase)
- [Linear → Azure Synapse](https://www.erathos.com/pipelines/linear-azure-synapse)
- [Linear → Amazon S3](/pipelines/linear-amazon-s3)

## Get started now

The Linear connector is available to all Erathos users. [Create your Erathos account](https://app.erathos.com/signup?slug=blog&button=cta&utm_campaign=linear_release) and connect your workspace in minutes, with no pipeline code to write, maintain, or monitor.