PostgreSQL IntegrationStart where your data already lives. No warehouse required.
The metrics that matter most are already in your PostgreSQL database: signups, orders, activation rates, churn, feature adoption. KPI Tree connects directly and adds what application dashboards cannot provide. Causal metric trees that map how every metric drives your outcomes, ownership at every level, statistical monitoring that catches shifts before they become problems, and personalised action plans that reach the people who can act. One scheduled query per metric. All analytics run off-database. Zero production impact. Works with Cloud SQL, RDS, Aurora, Supabase, Neon, and any database that speaks the PostgreSQL wire protocol.
Connected in under an hour
A guided setup wizard walks you through creating a read-only user with the minimum grants needed. No agents to install, no data extraction, no schema changes.
Create a read-only PostgreSQL user
The setup wizard generates copy-paste SQL that creates a dedicated user with SELECT privileges on your target schemas. No write access, no DDL, no superuser grants. Works with any PostgreSQL-compatible database: Cloud SQL, Amazon RDS, Aurora, Supabase, Neon, Crunchy Bridge, or self-hosted.
Authenticate and connect
Provide your host, port (default 5432), database name, username, and password. Optional SSL parameters (sslmode, sslcert, sslkey, sslrootcert) are available for environments that require client certificate authentication. KPI Tree validates the connection in real time. IP allow-listing is available so your database only accepts connections from KPI Tree's static IP.
Define metrics and start acting on them
Write SQL queries against your application tables to define each metric. One query per metric, executed on a configurable schedule. All downstream analytics run off-database in KPI Tree's engine. From there, map how metrics drive each other, assign ownership, and give every team member a reason to care about the numbers.
Map, measure, prove, act on the data you already have
Most metric platforms assume your data lives in a warehouse. For startups and growing teams, the metrics that matter most live in the application database. KPI Tree treats PostgreSQL as a first-class data source and adds the accountability layer your dashboards are missing.
One query per metric, all analytics off-database
Each metric runs a single SQL query on a configurable schedule. Correlations, comparisons, outlier detection, and causal analysis all run in KPI Tree's own engine. Your production database never takes on analytical workload, regardless of how many people are looking at the metrics.
Causal metric trees from your application data
Signups drive activations. Activations drive conversions. Conversions drive revenue. KPI Tree models these as parent-child trees with an owner at every node. When revenue dips, you follow the tree to the upstream metric that changed and the person who owns it.
Works with every PostgreSQL-compatible database
Cloud SQL, Amazon RDS, Aurora, Supabase, Neon, Crunchy Bridge, Aiven, or self-hosted PostgreSQL. If it speaks the PostgreSQL wire protocol, KPI Tree connects to it. No vendor-specific extensions, no custom drivers.
Your team does not need a warehouse to take metrics seriously.
Every other metric platform starts with "first, set up a data warehouse." That is a real barrier for startups and teams whose data lives in their application database. KPI Tree connects directly to PostgreSQL with a standard host, port, database, username, and password. No warehouse, no ETL, no six-month data infrastructure project. Define metrics with SQL against the tables you already have. Each metric gets an owner, trend analysis, statistical alerts, and a place in a causal tree that maps how your business actually works. Start where your data lives. Add a warehouse later if you need one.
- Connect with host, port, database, username, and password
- Each metric gets an owner, trend analysis, and statistical alerts
- No warehouse or ETL pipeline required to get started
- Works alongside warehouse integrations when you scale your data stack
Your production database stays protected. Full stop.
Connecting an analytics tool to a production database raises legitimate concerns. KPI Tree is designed to be a good citizen on production infrastructure. One scheduled query per metric, no additional queries for comparisons, aggregations, or user interactions. A read-only user that cannot modify data or schema. SSL available on every connection with optional client certificates for mutual TLS. IP allow-listing so the database accepts connections only from a known source. All computation happens off-database. The result: your operations team gets accountability metrics without putting production workload at risk.
- One query per metric on a configurable schedule, no additional queries for page loads or filters
- Read-only user with SELECT grants on chosen schemas only
- SSL with optional client certificate authentication (sslcert, sslkey, sslrootcert)
- All analytics computation runs off-database in KPI Tree's engine
Built for startups and teams whose metrics live in the app database.
Your product already generates the data you need: user signups, activation events, orders, subscription changes, feature usage, support tickets. KPI Tree connects to the PostgreSQL database your application writes to and turns that operational data into structured metric trees with ownership. No data team required. No warehouse prerequisite. Define the metrics that matter, assign an owner to each one, and start holding your team accountable to the numbers your product already produces.
- Signups, orders, activation rates, churn, and revenue are already in your tables
- No data team or warehouse prerequisite to get started
- Assign an owner to every metric and build causal trees from day one
- Add a warehouse later and your trees, ownership, and baselines carry over
Combine PostgreSQL data with every other source your business uses.
PostgreSQL rarely holds everything. Marketing spend lives in Google Ads. Pipeline data sits in your CRM. Support tickets come from your helpdesk. Financial data lands in your billing system. KPI Tree builds metric trees across all of it. A single tree can trace the path from ad spend to signup in PostgreSQL to activation to first payment, with an owner at every stage. That cross-source causal model is what single-tool dashboards cannot provide.
- PostgreSQL metrics in the same tree as warehouse, SaaS, and API metrics
- Correlation analysis across sources surfaces cross-functional relationships
- End-to-end accountability from acquisition to retention
- Each metric node carries ownership regardless of its data source
How KPI Tree uses PostgreSQL differently
Most tools either require a warehouse or treat the application database as a live query engine for dashboards. KPI Tree treats PostgreSQL as a data source, runs one query per metric on a schedule, and focuses on the problem dashboards never solve: getting people to act.
One query per metric, analytics off-database
KPI Tree runs one query per metric on a configurable schedule. Comparison periods, correlations, and analysis run in KPI Tree's compute engine without pushing additional queries to your database.
Trees, ownership, and action plans
PostgreSQL monitoring tools show you charts. KPI Tree arranges your business metrics into cause-and-effect trees with RACI ownership, tells every team member what changed and what to do next, then helps you prove whether the action worked. That is the difference between reporting and accountability.
Production-safe by design
Read-only user. SELECT-only grants. SSL with optional client certificates. IP allow-listing. One scheduled query per metric. KPI Tree was designed for the constraints of a production database, not built for a warehouse and bolted on afterwards.
Related integrations
Other data sources that work with KPI Tree.
Common questions
- Host, port (defaults to 5432), database name, username, and password. For environments that require client certificate authentication, you can also provide sslmode, sslcert, sslkey, and sslrootcert. The setup wizard validates the connection in real time before saving.
- No. KPI Tree connects directly to PostgreSQL as a database source. You can build metric trees, assign ownership, run statistical monitoring, and deliver personalised action plans with no warehouse at all. If you later add a warehouse like Snowflake or BigQuery, those metrics live in the same trees alongside your PostgreSQL metrics.
- Yes. KPI Tree works with any database that speaks the PostgreSQL wire protocol: Google Cloud SQL, Amazon RDS, Amazon Aurora, Supabase, Neon, Crunchy Bridge, Aiven, DigitalOcean Managed Databases, Azure Database for PostgreSQL, and self-hosted instances.
- No. KPI Tree runs one read-only query per metric on a configurable schedule. All downstream analytics, including correlations, comparisons, outlier detection, and causal analysis, run off-database. There are no per-user queries, no real-time streaming, and no write operations. The load on your database is predictable and minimal regardless of how many team members are using KPI Tree.
- A dedicated PostgreSQL user with SELECT privileges on the schemas containing the tables you want to query. No write access, no DDL, no superuser. The setup wizard generates the exact GRANT statements you need.
- Yes. KPI Tree supports SSL on all PostgreSQL connections, with optional client certificate authentication for mutual TLS (sslcert, sslkey, sslrootcert). IP allow-listing is available so your database firewall only accepts connections from KPI Tree's static IP. All credentials are encrypted at rest with HSM-backed KMS.
- Yes. If your dbt project runs against PostgreSQL, you can connect KPI Tree directly to the same database to query your dbt models. KPI Tree also has dedicated dbt Cloud and dbt Core integrations that sync metrics from your semantic layer automatically.
- Under an hour for most teams. Create the read-only user with the generated SQL, provide your host, port, database, username, and password, and KPI Tree validates the connection in real time. From there, define your first metrics and start building trees immediately.
Related guides
Deep dives into the frameworks and metrics that work with PostgreSQL.
Your application database already holds the metrics that matter.
Connect PostgreSQL to KPI Tree in under an hour. No warehouse needed. One query per metric, zero production impact, and an accountability layer that turns operational data into action across your entire organisation.
