1. Project Overview

ClkLog is an open-source software solution for recording and analyzing user behavior and user profiles. Developers can quickly complete private deployments. Based on the Sensors Analytics SDK, ClkLog uses the ClickHouse database to store collected data and adopts a frontend-backend separation architecture. With ClkLog, you can easily view user activity across websites, APPs, Mini Programs, and business systems. You can also gain comprehensive insights into users from multiple dimensions, including time, geographic location, channels, and visitor types. In addition to its open-source community edition, ClkLog also offers a commercial edition with more advanced analytics features.

2. Open Source License

Licensed under AGPL-3.0

3. Screenshots

Illustration

4. Feature Overview

ClkLog is a free, commercially usable, lightweight, fully open-source user analytics system based on event tracking. Licensed under the AGPL protocol, it is designed to help business teams and enterprises with technical development capabilities customize and extend the system. Developers can quickly build a privately deployed user analytics system with ClkLog to record and analyze user behavior, build user profiles, and combine them with business metrics to support refined business operations. It uses a mature open-source software architecture and widely adopted mainstream components: Frontend (vue, vue-element-admin, element-ui, echarts), Backend (Redis, Zookeeper, Kafka, Flink).

5. Tech Stack

Technology Stack Selection

• Backend: Redis, Zookeeper, Kafka, Flink

• Frontend: vue, vue-element-admin, element-ui, echarts

• Data: Clickhouse

ClickHouseClickHouse is a column-oriented database management system specifically designed for high-performance data analytics and data warehousing applications. It is an open-source database system originally developed by the Russian search engine company Yandex to meet the demands of large-scale data analysis and reporting.

Features

• An open-source column-oriented database management system featuring linear scalability, simplicity, convenience, and high reliability.

• Fast Fault-Tolerant Processing and Benchmark Performance: Capable of processing data at a scale of billions of records.

• Rich Features: Supports various data analytics and statistical scenarios, SQL-like queries, and cross-region replication and deployment.

Kafka Kafka is an open-source stream processing platform developed by the Apache Software Foundation and written in Scala and Java. Kafka is a high-throughput distributed publish-subscribe messaging system that can process all activity streams generated by consumers on a website. These activities, including page views, searches, and other user actions, are key elements of many social features on modern websites. Due to throughput requirements, this data is typically handled through log processing and log aggregation. Kafka provides a viable solution for scenarios that require real-time processing, where traditional log data and offline analytics systems such as Hadoop are insufficient. Kafka aims to unify online and offline message processing through Hadoop's parallel loading mechanism while also providing real-time messaging through clustering.

Apache Flink Flink is an open-source stream processing framework developed by the Apache Software Foundation. Its core is a distributed data streaming engine written in Java and Scala. Flink executes arbitrary data stream programs using data parallelism and pipelining. Its pipelined runtime system can execute both batch processing and stream processing programs. In addition, Flink's runtime natively supports the execution of iterative algorithms.