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DataDog/dd-trace-java

Datadog APM client for Java

Java ◇ apm Apache-2.0
★737STARS
⑂362FORKS
!481ISSUES
🏆#3,147GLOBAL RANK
🔥3DAYS TRENDING
🚀
Maintainer Growth Kit for dd-trace-java

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Star History

Continuous Observations
Interactive star growth chart for DataDog/dd-trace-java
CSV

Momentum

+18

STARS · LAST 30 DAYS

1

PER DAY

#232

MOST-STARRED Java

Window7 days30 days90 days
Stars gained+7+18+90
Per day111
Forks gained+2+7+18

dd-trace-java gained 18 stars in the last 30 days, about 1 a day, and now has 737. It is about 9 years old and has averaged roughly 82 stars a year. It ranks #232 among Java repositories and #3,147 across all languages on GitHubRepo.

Trending Record

dd-trace-java has maintained a continuous presence across global trending indexes, peaking at #2348. Below is the 30-day activity profile:

💡 Overview

dd-trace-java is an open-source project written in Java: Datadog APM client for Java.

Engineered for speed, consistency, and developer ease, it solves common hurdles in apm, bytebuddy, datadog. It provides clear interfaces, comprehensive configuration options, and seamless integration with existing tools across the modern development stack.

⚡ Key Features

1

Optimized execution pipeline written in Java for predictable speed.

2

Zero-friction configuration with comprehensive sensible defaults out of the box.

3

Cross-platform runtime support across Linux, macOS, and Windows environments.

4

Strong typing and modular architecture designed for easy extension and maintainability.

5

Standardized CLI and API interfaces for smooth integration into CI/CD workflows.

6

Active community maintenance with regular dependency updates and security patches.

📥 Installation

terminal
$ git clone https://github.com/DataDog/dd-trace-java.git
cd dd-trace-java

⚙ System Requirements

Platforms

  • • macOS
  • • Linux
  • • Windows

Runtime & Dependencies

JDK 17 or higher (OpenJDK / GraalVM)

Architecture

x86_64, ARM64 (Apple Silicon & Graviton)

🧠 How It Works

dd-trace-java coordinates its core functionality through a modular Java pipeline. It parses configuration parameters, validates inputs, and resolves dependencies asynchronously. By minimizing runtime overhead and keeping allocations localized, it delivers predictable performance in both local development environments and automated production workloads.

🎯 Production Use Cases

Autonomous AI Agents

Orchestrate intelligent workflows and tool-calling routines with dd-trace-java.

Model Inference & Prompting

Integrate fast, local or cloud-hosted generative AI models directly into production code.

Context Memory & RAG

Augment language models with dynamic vector retrieval and structured project memory.

Developer Productivity

Automate repetitive engineering tasks, code generation, and test creation using AI agents.

🚀 Getting Started

1

Install dd-trace-java using your package manager: `git clone https://github.com/DataDog/dd-trace-java.git`

2

Initialize your project workspace or configuration file for dd-trace-java.

3

Import dd-trace-java into your codebase or invoke it directly from your terminal.

4

Execute your test suite or run `dd-trace-java --help` to verify successful setup.

👍 Strengths

Active community backing with 737 GitHub stars and verified adoption.
Permissive open-source distribution under the Apache-2.0 license.
Built in Java for high execution speed and developer familiarity.
Cross-platform compatibility across modern Linux, macOS, and Windows environments.
Clean modular design allowing flexible configuration and pipeline integration.

⚠️ Considerations

Requires familiarity with Java and modern CLI workflows.
Ecosystem extensions may require manual configuration depending on environment constraints.
Active development roadmap means breaking API changes may occur across major versions.

⇄ Alternatives & Direct Competitors

💡
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Explore all Datadog alternatives →
S

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👥 Who Should Use This

Developers and engineering teams building with Java, seeking reliable, tested, and actively maintained tooling for production workloads.

🏆 Nearby in the Rankings

DataDog/dd-trace-java is currently ranked #3,147 by stars across every repository tracked on GitHubRepo. These are adjacent projects:

RankRepositoryLanguageStarsAction
#3,142 nextcloud/notes JavaScript ★ 740 Compare ↗
#3,142 Azure/bicep-registry-modules Bicep ★ 740 Compare ↗
#3,142 eerimoq/moblin Swift ★ 740 Compare ↗
#3,142 ProdigyV21/ARVIO Kotlin ★ 740 Compare ↗
#3,142 OpenMOSS/MOSS-VL C++ ★ 740 Compare ↗
#3,147 DataDog/dd-trace-java This Project Java ★ 737
#3,147 FooBarWidget/default_value_for Ruby ★ 737 Compare ↗
#3,147 KKeygen/idv-login Python ★ 737 Compare ↗
#3,147 dahlia/optique TypeScript ★ 737 Compare ↗
#3,151 iblai/os TypeScript ★ 736 Compare ↗
#3,151 okf-memory/okf-agent-memory Go ★ 736 Compare ↗

Frequently Asked Questions

What does dd-trace-java do? +

Datadog APM client for Java

What language is dd-trace-java written in? +

The primary language is Java. Topics include: apm, bytebuddy, datadog, datadog-apm, datadoghq.

Is dd-trace-java actively maintained? +

Yes, the last recorded push was on Sep 28, 2026 with 481 open issues being tracked.

How many stars does dd-trace-java have? +

dd-trace-java has 737 stars and 362 forks on GitHub.

How does dd-trace-java rank among GitHub repositories? +

With 737 stars, DataDog/dd-trace-java is ranked #3,147 globally across all repositories tracked on GitHubRepo and #232 among Java projects.

What license is dd-trace-java distributed under? +

The repository reports a Apache-2.0 license. Always verify the repository LICENSE file for legal terms.

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