Best 7 Open-Source Mixes (analytics + BI + dashboards) That Teams Use to Replicate Countly-Style Reports With Custom Visualizations

Modern analytics needs are more complex than ever. Companies want a mix of dashboards, custom visualizations, and real-time reporting capabilities while retaining full control over their data. Solutions like Countly have gained popularity by offering product analytics and strong customization features. But what if your team wants to use open-source tools to replicate—or even exceed—what Countly-style reporting offers?

TLDR:

Looking to replicate Countly-style analytics using open-source solutions? We’ve rounded up the best 7 open-source mixes that, when combined, create powerful Business Intelligence (BI) systems with custom dashboards, real-time data capabilities, and extensive visualization options. Whether you’re building a product analytics suite or modernizing your internal reporting stack, these tools are flexible, scalable, and community-driven. And yes—they’re budget-friendly too!

Why Consider Countly Alternatives?

Countly is an excellent tool for direct product analytics, crash analytics, and customer engagement metrics. However, it may not suit every organization, especially those with security constraints, custom data processing needs, or a preference for open-source ecosystems. Open-source stacks offer:

• Data ownership and privacy
• Customization at every layer (UI, query engine, storage)
• Cost control and no vendor lock-in
• Community support and extensive integrations

Let’s explore seven high-impact open-source tools and how teams are combining them to create robust, Countly-style BI and analytics stacks.

1. Apache Superset – Real-Time BI Dashboards

Apache Superset is a powerful, open-source data exploration and visualization platform designed for creating rich dashboards and real-time analytics. Developed at Airbnb and donated to the Apache Foundation, it’s now widely used as an enterprise-grade BI platform.

Why teams love it:

• SQL Lab for ad hoc queries
• Plugin support for custom visualizations
• Role-based access control
• Integration with most SQL-based databases

When paired with a real-time data pipeline tool (like Apache Kafka or Redpanda), Superset powers analytics dashboards that are both robust and near real-time—ideal for tracking user behavior and KPIs.

2. Metabase – Simpler and User-Friendly UI for Internal Teams

For teams that want simplicity and minimal setup, Metabase offers a sleek, intuitive UI that’s almost plug-and-play. With easy filtering, drill-downs, and natural-language queries (“Ask a question” feature), it democratizes data.

What stands out:

• Beautiful dashboards in minutes without needing code
• Can be embedded into internal portals or customer interfaces
• Built-in scheduler for email and Slack reporting

As a frontend dashboard tool, Metabase shines when plugged into a traditional PostgreSQL, MySQL, or ClickHouse data store—bringing an elegant viewer to back-end heavy data pipelines.

3. Redash – Collaborative SQL-Based Analytics

Redash is an open-source tool known for integrating with everything from PostgreSQL to NoSQL databases like MongoDB and Elasticsearch. It’s perfect for SQL-savvy teams that want precise control of analytic workflows without compromising on visualization quality.

Best suited for:

• Teams who are hands-on with SQL
• Sharing quick visualizations across departments
• Managing queries and dashboards via APIs

Many engineering-focused companies choose Redash when flexibility and backend agnosticism are the highest priorities.

4. Lightdash + dbt – Modern Looker Alternative for Metrics Layer

If you’ve heard of Looker, then Lightdash will feel familiar. Combined with dbt (Data Build Tool), it creates an analytics framework where business logic lives in version-controlled code, making dashboards consistent and easy to audit.

Benefits:

• Centralized metrics definitions
• Git-based collaboration
• Smooth UI for non-technical users

Lightdash is particularly useful for SaaS companies and data teams who want repeatable, error-proof data models exposed to business users as simple dashboards.

5. Grafana – Data Observability Focused with Strong Dashboarding

Though often associated with DevOps and system monitoring, Grafana also excels at business data visualization. When connected to analytics stores like ClickHouse, PostgreSQL, or even Google BigQuery, Grafana can support product usage tracking and real-time metrics analysis.

Features worth noting:

• Fast, customizable visualizations with alerts
• Support for mixed data sources
• Flexible plugin architecture

Combining Grafana with time-series databases like Prometheus or InfluxDB allows you to display customer journeys, error trends, and feature adoption over time.

6. Jitsu + ClickHouse – Open-Source Event Tracking + Storage Solution

For teams specifically looking to replicate Countly’s product analytics component (i.e., tracking user events, clicks, paths, and sessions), a powerful combination is Jitsu as an event ingestion layer paired with ClickHouse as the high-speed OLAP database.

Advantages:

• Jitsu’s real-time event tracking is JavaScript and mobile SDK friendly
• ClickHouse enables massive-scale querying of behavioral event logs
• Full transparency of data flow and schema handling

Add Superset or Grafana on top of this stack to generate quick product-level KPIs like active users, retention curves, and conversion funnels.

7. PostHog – The All-in-One Product Analytics Platform

One open-source contender that wants to be a one-stop solution is PostHog. It directly competes with Countly by offering features like session recording, feature flags, and user tracking—all self-hostable.

Why teams go with PostHog:

• Comprehensive SPA and mobile tracking
• Funnels, path analysis, trends built-in
• Modern UI with active community plugins

PostHog is a favorite for startups and mid-size product teams who want analytics out-of-the-box without much setup while maintaining full data ownership.

How to Mix & Match These Tools Effectively

These tools aren’t mutually exclusive. In fact, their power is amplified when combined into a modern analytics pipeline. Here’s a common open-source analytics architecture that mimics Countly:

• Event Tracking: Jitsu or PostHog
• Storage: ClickHouse or PostgreSQL
• Transformation: dbt or Apache Airflow
• Visualization: Superset, Metabase, or Lightdash

With this stack, your team gets the freedom to tailor front-end dashboards to different stakeholders, define custom metrics, and analyze user data with precision.

Final Thoughts

Countly is great, but the open-source world is rich with flexible, scalable, and community-supported tools. Whether you’re just getting started with product analytics or migrating from a proprietary solution, these 7 tools can build a fully customizable stack that’s tailored to your team’s needs.

Bonus tip: Don’t forget to contribute back! All these platforms thrive from open-source communities, so your team’s improvements could help thousands of others.