Bazel vs Gradle

Choosing the Right Build Tool

Build tools serve as the backbone of modern software development, transforming source code into deployable applications. This comprehensive comparison examines two leading build tools, Bazel and Gradle, to help enterprise decision-makers understand which solution best fits their specific needs and organizational requirements.

Introduction to Bazel

Bazel is an open-source build and test tool developed by Google that can handle large codebases and multiple programming languages efficiently. It uses a declarative build language to define build targets and their dependencies, enabling fast incremental builds by only rebuilding what has changed. Bazel is particularly well-suited for monorepos and complex projects where build speed and reproducibility are critical concerns.

Overview

What is Bazel

Bazel represents Google's solution to a problem few companies face: managing a codebase with billions of lines of code and tens of thousands of developers. Born from Google's internal build system called Blaze in 2006, Bazel was open-sourced in March 2015 to share its unique capabilities with the broader developer community.

At its core, Bazel operates on principles of hermeticity and reproducibility. This means that given the same source code inputs, Bazel will always produce identical outputs, regardless of the machine or environment where the build runs. This predictability becomes invaluable when coordinating work across large teams and ensuring consistent deployments.

Hermetic and Reproducible Builds

Bazel's foundational principle is hermetic build isolation. By sandboxing build actions and tracking every input dependency, Bazel ensures that builds depend only on explicitly declared inputs. This isolation eliminates the dreaded "works on my machine" problem and enables powerful distributed build capabilities.

Connect dots with check marks

Remote Caching and Execution

Bazel's architecture revolves around a directed acyclic graph (DAG) of build targets and their dependencies. The system analyzes these dependencies to determine the minimal set of actions needed for any given build, enabling impressive parallelization and remote caching capabilities that scale across distributed teams.

A diagram that shows the Bazel communicating with the bazel-remote service and its multiple backend options.

Multi-Language Support

Bazel's language and platform agnostic design allows organizations to use a single build system across their entire technology stack. Whether building Java services, C++ libraries, Go microservices, Python data pipelines, or JavaScript frontends, Bazel provides a unified interface and consistent developer experience.

# Java and Node.js BUILD.bazel file example

load("@rules_java//java:defs.bzl", "java_binary", "java_library", "java_test")
load("@build_bazel_rules_nodejs//:index.bzl", "nodejs_binary", "npm_package_bin")
load("@npm//@bazel/typescript:index.bzl", "ts_library")

# Java library and binary
java_library(
    name = "user_service",
    srcs = ["src/main/java/com/example/UserService.java"],
    deps = [
        "@maven//:com_google_guava_guava",
        "@maven//:org_springframework_spring_core",
        "@maven//:com_fasterxml_jackson_core_jackson_core",
    ],
    visibility = ["//visibility:public"],
)

java_binary(
    name = "java_backend",
    srcs = ["src/main/java/com/example/BackendApp.java"],
    deps = [":user_service"],
    main_class = "com.example.BackendApp",
)

java_test(
    name = "user_service_test",
    srcs = ["src/test/java/com/example/UserServiceTest.java"],
    deps = [
        ":user_service",
        "@maven//:junit_junit",
        "@maven//:org_mockito_mockito_core",
    ],
    test_class = "com.example.UserServiceTest",
)

# TypeScript/Node.js library
ts_library(
    name = "api_client",
    srcs = ["src/frontend/api-client.ts"],
    deps = [
        "@npm//@types/node",
        "@npm//axios",
    ],
    visibility = ["//visibility:public"],
)

ts_library(
    name = "frontend_app",
    srcs = [
        "src/frontend/app.ts",
        "src/frontend/components/user-list.ts",
    ],
    deps = [
        ":api_client",
        "@npm//@types/express",
        "@npm//express",
    ],
)

# Node.js binary
nodejs_binary(
    name = "node_server",
    data = [":frontend_app"],
    entry_point = "src/frontend/app.js",
    node_modules = "@npm//:node_modules",
)

# Build frontend assets
npm_package_bin(
    name = "webpack_bundle",
    tool = "@npm//webpack-cli:bin",
    data = [
        ":frontend_app",
        "webpack.config.js",
        "@npm//:node_modules",
    ],
    output_dir = True,
    args = ["--mode=production"],
)

# Protocol Buffers shared between Java and Node.js
load("@rules_proto//proto:defs.bzl", "proto_library")
load("@rules_java//java:defs.bzl", "java_proto_library")

proto_library(
    name = "api_proto",
    srcs = ["proto/api.proto"],
    visibility = ["//visibility:public"],
)

java_proto_library(
    name = "api_java_proto",
    deps = [":api_proto"],
)

# Generate TypeScript definitions from proto
genrule(
    name = "api_ts_proto",
    srcs = [":api_proto"],
    outs = ["proto/api_pb.d.ts"],
    cmd = "$(execpath @npm//protoc-gen-ts:bin) --proto_path=. --ts_out=$(@D) $(SRCS)",
    tools = ["@npm//protoc-gen-ts:bin"],
)

# File groups for shared resources
filegroup(
    name = "static_assets",
    srcs = glob(["static/**/*"]),
    visibility = ["//visibility:public"],
)

filegroup(
    name = "config_files",
    srcs = [
        "application.properties",
        "package.json",
        "tsconfig.json",
    ],
    visibility = ["//visibility:public"],
)

# Integration test that uses both Java and Node.js components
sh_test(
    name = "integration_test",
    srcs = ["test/integration_test.sh"],
    data = [
        ":java_backend",
        ":node_server",
        ":static_assets",
    ],
    size = "medium",
)

What are the trade offs?

Let’s take a look at the advantages and disadvantages of choosing Bazel.

Advantages

Here are the advantages of using Bazel.

  1. Scalability: Bazel handles codebases with millions of files and supports thousands of concurrent developers. Its incremental build capabilities scale linearly, meaning build times grow proportionally with change size rather than codebase size.
  2. Monorepo Support: Organizations like Spotify reduced iOS build times from 80 minutes to 20 minutes—a 4x improvement. Uber's Go monorepo with 900+ active developers and 70,000+ files operates smoothly thanks to Bazel's scalability.
  3. Cross-Language Dependencies: Dropbox successfully uses Bazel for production releases across TypeScript, Python, Go, C, and Rust—all in one unified build system.
  4. Remote Execution: Rather than being limited by local machine resources, teams can elastically scale build capacity using remote execution services, enabling build times that would be impossible with traditional approaches.
  5. Comprehensive Testing: Bazel automatically determines which tests are affected by code changes, dramatically reducing CI times through remote test execution, result caching, and built-in flaky test detection.

Disadvantages

Here are the disadvantages of using Bazel.

  1. Steep Learning Curve: Migration from existing build systems demands significant engineering effort—organizations report 6-24 month timelines for large codebases. The need to understand Starlark, BUILD file maintenance, and hermetic build concepts overwhelms many teams.
  2. Maintenance Overhead: Verbose BUILD files must be manually maintained for each package. Unlike tools that use convention-based discovery, Bazel requires explicit declaration of all dependencies and build rules.
  3. Limited Ecosystem: With only 120+ rules compared to Gradle's 4,300+ plugins, teams often need to write custom rules for specialized requirements. IDE support remains limited.
  4. Poor Fit for Small Projects: Industry experts recommend against Bazel for codebases under 1 million lines of code or single-language repositories. The complexity simply isn't justified by the benefits at smaller scales.
  5. Infrastructure Requirements: Achieving Bazel's promised performance often requires significant investment in remote build execution infrastructure, cache storage, and dedicated build machines.

Introduction to Gradle

Gradle is a powerful build automation tool primarily used for Java, Android, and other JVM-based projects, though it supports multiple programming languages. It uses a domain-specific language (DSL) based on Groovy or Kotlin to define build scripts, making it more flexible and readable than XML-based tools like Maven or Ant. Gradle efficiently manages dependencies, compiles code, runs tests, and packages applications while offering features like incremental builds and build caching to improve performance.

Overview

What is Gradle

Gradle emerged in 2007-2008 from developer Hans Dockter's vision for a more flexible alternative to existing build tools. After years of development and refinement, Gradle 1.0 launched in June 2012, quickly gaining adoption in the Java ecosystem as the official build tool for Android development.

Unlike Bazel's focus on massive scale, Gradle prioritizes developer experience and flexibility. The tool embraces a "convention over configuration" philosophy, providing sensible defaults while allowing complete customization when needed.

Flexible Build Scripts

Gradle's technical foundation rests on a sophisticated directed acyclic graph (DAG) for managing task dependencies. The system operates in three distinct phases: initialization, configuration, and execution, enabling optimal parallel execution and intelligent caching strategies.

Lots of connected dots

Groovy and Kotlin DSL

Gradle provides powerful configuration capabilities through both Groovy and Kotlin DSL options. While Groovy DSL offers dynamic, concise syntax, the newer Kotlin DSL brings static typing, superior IDE support with code completion, and compile-time error checking.

plugins {
    id("java")
    id("application")
}

group = "com.example"
version = "1.0.0"

repositories {
    mavenCentral()
}

dependencies {
    implementation("org.apache.commons:commons-lang3:3.12.0")
    testImplementation("org.junit.jupiter:junit-jupiter:5.9.2")
    testRuntimeOnly("org.junit.platform:junit-platform-launcher")
}

application {
    mainClass.set("com.example.Main")
}

tasks.test {
    useJUnitPlatform()
}

tasks.jar {
    manifest {
        attributes["Main-Class"] = "com.example.Main"
    }
}

java {
    toolchain {
        languageVersion.set(JavaLanguageVersion.of(11))
    }
}

Performance Optimization

The Gradle Daemon eliminates JVM startup costs by maintaining a persistent background process. Combined with incremental compilation, parallel execution, and sophisticated local and remote caching, Gradle can reduce build times by up to 90% compared to traditional approaches.

Build model

What are the trade offs?

Let’s take a look at the advantages and disadvantages of choosing Gradle.

Advantages

Here are the advantages of using Gradle.

  1. Developer Experience: Native IDE integration in IntelliJ IDEA, Android Studio, Eclipse, and VS Code means developers can start working immediately without learning new tools.
  2. Plugin Ecosystem: With over 4,300 community plugins available, developers can integrate virtually any tool or technology into their build process.
  3. Dependency Management: Gradle handles complex real-world scenarios elegantly with sophisticated conflict resolution, version catalogs for centralized dependency management, and support for multiple repository types.
  4. Performance: Recent benchmarks show Gradle outperforming Bazel by 5-16x for incremental builds in many scenarios.
  5. Adoption: Unlike Bazel's "all-in" approach, Gradle supports incremental adoption. Teams can start with simple builds and gradually adopt advanced features like remote caching or test distribution.

Disadvantages

Here are the disadvantages of using Gradle.

  1. Learning Curve for Advanced Features: While basic Gradle usage is straightforward, mastering the DSL, understanding the plugin ecosystem, and optimizing build performance requires significant investment.
  2. JVM Performance Impact: JVM startup costs impact quick builds, and large multi-project builds can suffer from slow configuration phases. Memory consumption for extensive project hierarchies sometimes requires careful tuning.
  3. Dependency Resolution Complexity: Gradle's sophisticated dependency resolution can sometimes produce unexpected results. Plugin compatibility issues during version upgrades force teams to delay updates.
  4. Tool Integration Variability: While Gradle excels in IntelliJ IDEA and Android Studio, support in other IDEs varies significantly. Debugging build scripts remains challenging.
  5. Enterprise Standardization: The same configurability that enables powerful customizations can lead to inconsistent build patterns across teams. Organizations wanting advanced features face vendor lock-in with Gradle Enterprise licensing.

How do Bazel and Gradle compare?

Selecting between Bazel and Gradle typically depends on your project's unique needs and your team's technical expertise. Comparing how these tools perform across various aspects enables a well-informed choice.

Performance and Build Times

Build performance directly impacts developer productivity and CI/CD pipeline efficiency. This section compares how each build system handles different workload types and project scales.

Gradle

Gradle consistently outperforms Bazel in real-world enterprise scenarios for typical Java projects, achieving 5-16x faster incremental builds. The platform's mature optimization techniques and familiar build model provide immediate performance benefits for most development teams.

Bazel

However, Bazel excels at massive scale—organizations with codebases exceeding 100 million lines of code report better performance with Bazel's fine-grained caching and remote execution capabilities. The platform's architecture becomes increasingly advantageous as project complexity grows.

Developer Experience and IDE Integration

The daily development experience significantly affects team productivity and adoption rates. This section examines how each build system integrates with common development workflows and tooling.

Gradle

Gradle wins decisively in developer experience with native IDE integration, familiar concepts for Java developers, and extensive documentation creating a gentle onboarding experience. The platform's conventional approach reduces the learning curve for most development teams.

Bazel

Bazel's explicit dependency management and hermetic builds provide stronger correctness guarantees but require developers to think differently about builds. The need to maintain BUILD files, understand Starlark, and debug sandboxed builds creates ongoing friction for development teams.

Scalability and Monorepo Support

Large-scale development requires build systems that can handle complex dependency graphs and massive codebases efficiently. This section compares architectural approaches to scalability.

Gradle

Gradle handles large codebases effectively but takes a different approach. Rather than requiring monorepos, Gradle's composite builds support both monorepo and multi-repo strategies, providing flexibility for organizations with hundreds rather than thousands of developers.

Bazel

Bazel's design shines for massive monorepos. Google's success with 2+ billion lines of code proves Bazel's scalability through fine-grained dependency tracking, true incrementality, and distributed execution capabilities.

Integration Ecosystem

The availability of pre-built integrations affects implementation speed and maintenance overhead. This section examines the maturity and breadth of each platform's ecosystem.

Gradle

Gradle's mature ecosystem provides significant advantages with 4,300+ plugins offering pre-built integrations for virtually any tool or workflow. CI/CD pipelines, security scanners, and deployment tools integrate seamlessly with minimal configuration effort.

Bazel

Bazel's smaller ecosystem (120+ rules) means teams often write custom integrations. While Bazel's rules are high-quality, the limited selection increases implementation effort. However, Bazel's multi-language support sometimes provides cleaner integration than Gradle's plugin-based approach.

Build Reproducibility

Consistent build results across different environments are crucial for reliable software delivery. This section compares how each system ensures reproducible builds.

Gradle

Gradle offers good reproducibility features but doesn't match Bazel's strict isolation guarantees. However, for most enterprise applications, Gradle's reproducibility level is sufficient while offering better developer productivity.

Bazel

Bazel provides superior build reproducibility through hermetic builds that eliminate environment-specific issues. This "correctness by construction" approach means builds succeed consistently across development, CI, and production environments.

Which tool should you pick?

Your choice between Bazel and Gradle should match your team's needs, existing toolchain, and operational priorities.

Choose Bazel when you have:

  1. Ultra-large monorepos with 5+ million lines of code
  2. Multi-language microservices with complex interdependencies
  3. High-frequency development environments making hundreds of daily commits
  4. Mobile applications at scale requiring complex iOS/Android builds
  5. Security-critical systems requiring strict build reproducibility
  6. Platform engineering teams supporting thousands of developers

Chose Gradle when you have:

  1. Java/JVM microservices and Spring Boot applications
  2. Android application development projects
  3. Multi-platform Kotlin projects targeting multiple platforms
  4. Legacy modernization initiatives requiring gradual migration
  5. Regulated industries needing dependency management and security scanning
  6. Rapid development environments where time-to-market is critical

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