Krenalis is a Customer Data Platform (CDP) that helps data analysts and the marketing team collect, enrich, unify, and activate user and customer data — including product events, marketing signals, and sales interactions — and syncs it to the tools your teams use every day.

Krenalis is open and free to use. It's a lightweight, developer-friendly alternative to Customer Data Platforms such as Segment, RudderStack, and mParticle.

It is built in Go with a modern TypeScript/React frontend and a comprehensive REST API, and ships as a single executable that includes:

• Real-time event collection and dispatch
• Batch data ingestion from SaaS apps, databases, and files
• Transformations with Visual Mapping, JavaScript, or Python
• Identity resolution that runs directly inside your data warehouse
• A unified, 360-degree customer profile view
• Activation of profiles and events to SaaS apps, databases, and files
• Snowflake and PostgreSQL support as primary event and profile data storage

Krenalis unifies customer data across your entire stack without relying on traditional one-to-one integrations, which often introduce fragmentation and maintenance overhead as systems scale. It provides end-to-end visibility into the customer data pipeline and gives you fine-grained control over data modeling, enrichment logic, and downstream delivery.

Your customer data lives directly in your data warehouse, with native support for Snowflake and PostgreSQL. Identity resolution also runs inside the warehouse, allowing you to maintain a consistent and reproducible customer graph using the infrastructure you already trust.

This architecture is especially well-suited for AI workloads. Both AI agents and models can consume clean, unified, and continuously updated customer data directly from your warehouse, without additional pipelines.

Meanwhile, real-time, bidirectional sync keeps operational tools aligned with warehouse state — reducing operational burden, improving data reliability, and eliminating the need for separate data pipelines or orchestration layers.

The easiest way to collect events is to use one of the official SDKs:

• JavaScript (Browser) — https://github.com/krenalis/analytics-javascript
• Android — https://github.com/krenalis/analytics-kotlin
• iOS — https://github.com/krenalis/analytics-swift
• Python — https://github.com/krenalis/analytics-python
• .NET — https://github.com/krenalis/analytics-dotnet
• Java — https://github.com/krenalis/analytics-java
• Node.js — https://github.com/krenalis/analytics-nodejs
• Go — https://github.com/krenalis/analytics-go

For full documentation, visit https://www.krenalis.com/docs

To evaluate Krenalis locally, you can run a complete instance without setting up the full environment.

It includes the standalone krenalis executable, along with Node.js and Python for local transformations, and a PostgreSQL database—provided for convenience as both the internal support store and an optional warehouse for event and profile data.

Navigate to the directory where you want to run Krenalis and execute:

mkdir -p storage
curl -fO "https://raw.githubusercontent.com/krenalis/krenalis/refs/tags/v0.42.0/compose.yaml"
if [ ! -f .env ]; then printf "KRENALIS_KMS=key:%s\n" "$(openssl rand -base64 32)" > .env; fi
docker compose up

To build the standalone executable, run go generate && go build in the root directory of this repository:

1. Install Go 1.26 (if you haven't already)
2. Clone or download this repository
3. Check out the latest release
4. Run go generate
5. Run go build (See also https://go.dev/doc/install/source#environment)

To run the executable, provide an empty PostgreSQL database on first run, starting the krenalis command:

1. Generate and set KRENALIS_KMS, together with your PostgreSQL credentials, using the recommended environment variables. For a key-based KMS provider, use key:<base64-encoded 32-byte key> and keep the same value for the lifetime of the installation.
2. Run ./krenalis -init-db-if-empty

We take the security of Krenalis and its ecosystem seriously.

If you discover a potential vulnerability, please report it privately to security@krenalis.com rather than opening a public issue. See the SECURITY file for details.

We will acknowledge your report as quickly as possible and keep you updated throughout the resolution process. Valid reports will be credited in the release notes once the fix is published.

Krenalis is an open, community-driven project. We welcome contributions from developers of all backgrounds — whether you're fixing a bug, improving documentation, or building a new connector.

• Contributing to the source code
• Suggesting new features and reporting issues

To keep the project coherent and maintainable, we follow a roadmap and prioritize issues in a specific order. For this reason, please open an issue or discussion before submitting a pull request for a new feature.

Krenalis is licensed under the MIT License (for connectors and warehouse integrations) and the Elastic 2.0 License (for the core and admin). Both licenses are documented in the LICENSE file. You are free to use, modify, and integrate the project according to the terms described there.