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  1. Stackups
  2. DevOps
  3. Log Management
  4. Logging Tools
  5. CocoaLumberjack vs SwiftyBeaver

CocoaLumberjack vs SwiftyBeaver

OverviewComparisonAlternatives

Overview

CocoaLumberjack
CocoaLumberjack
Stacks57
Followers34
Votes0
GitHub Stars13.3K
Forks2.3K
SwiftyBeaver
SwiftyBeaver
Stacks7
Followers18
Votes0

CocoaLumberjack vs SwiftyBeaver: What are the differences?

Introduction

CocoaLumberjack and SwiftyBeaver are both popular logging frameworks in the Swift community. While they serve the same purpose of logging messages, they have key differences in terms of features and functionality.

  1. Customization Options: CocoaLumberjack offers a range of customization options, allowing developers to configure log levels, formatters, and destinations. It provides flexibility in choosing output formats and enables the use of multiple loggers simultaneously. On the other hand, SwiftyBeaver provides a simplified approach to logging with predefined log levels and destinations. While it may lack the same level of customization as CocoaLumberjack, it offers ease of use and simplicity for developers.
  2. Integration with Swift: SwiftyBeaver is specifically designed for Swift and takes advantage of its language features. It offers a more Swifty syntax for logging, making it easier for Swift developers to adopt and integrate into their projects. CocoaLumberjack, on the other hand, is a more mature framework that supports multiple languages, including Objective-C and Swift.
  3. Log Storage and Remote Logging: CocoaLumberjack provides built-in log storage functionality, allowing logs to be saved locally for later analysis. It also offers various appenders to send log messages to remote servers. SwiftyBeaver, on the other hand, does not have built-in log storage capability. It focuses more on real-time logging and forwarding log messages to designated destinations, such as the console or external logging services.
  4. Community and Support: CocoaLumberjack has been around for a longer time and has a large and active user community. This means there are more resources, documentation, and community-driven extensions available for developers using CocoaLumberjack. SwiftyBeaver, while gaining popularity, may have a smaller user community and fewer available resources in comparison.
  5. Additional Features: CocoaLumberjack offers additional features such as log message filtering based on regular expressions and log rolling for managing log files. It also provides more advanced features like hierarchical logging and logging context. SwiftyBeaver, on the other hand, focuses on simplicity and ease of use, with fewer additional features. This streamlined approach may be preferred by developers who want a straightforward logging solution without complexity.
  6. Compatibility with Existing Projects: CocoaLumberjack can easily integrate into existing projects that already use it or other logging frameworks. It offers seamless compatibility, making it easier to transition from other logging frameworks. SwiftyBeaver, being a more specialized framework for Swift, may require more effort to integrate into existing projects that are not already using it.

In summary, CocoaLumberjack and SwiftyBeaver differ in customization options, Swift integration, log storage capabilities, community support, additional features, and compatibility with existing projects. Developers can choose between the flexibility and maturity of CocoaLumberjack or the simplicity and Swifty syntax of SwiftyBeaver based on their specific logging requirements and preferences.

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Detailed Comparison

CocoaLumberjack
CocoaLumberjack
SwiftyBeaver
SwiftyBeaver

CocoaLumberjack is a fast & simple, yet powerful & flexible logging framework for Mac and iOS.

It is Swift-based logging framework for iOS and macOS. It has different types of log messages where also we can filter logs to make bug checking even easier and has a free license plan.

-
Time (with microsecond precision); Level (output in color); Thread name (if not main thread); Filename, function & line; Message (can be string or a variable of any type)
Statistics
GitHub Stars
13.3K
GitHub Stars
-
GitHub Forks
2.3K
GitHub Forks
-
Stacks
57
Stacks
7
Followers
34
Followers
18
Votes
0
Votes
0
Integrations
No integrations available
Swift
Swift
Xcode
Xcode
SQLite
SQLite
macOS
macOS

What are some alternatives to CocoaLumberjack, SwiftyBeaver?

Seq

Seq

Seq is a self-hosted server for structured log search, analysis, and alerting. It can be hosted on Windows or Linux/Docker, and has integrations for most popular structured logging libraries.

Loki

Loki

Loki is a horizontally-scalable, highly-available, multi-tenant log aggregation system inspired by Prometheus. It is designed to be very cost effective and easy to operate, as it does not index the contents of the logs, but rather a set of labels for each log stream.

Log4j

Log4j

It is an open source logging framework. With this tool – logging behavior can be controlled by editing a configuration file only without touching the application binary and can be used to store the Selenium Automation flow logs.

Castle Core

Castle Core

It provides common Castle Project abstractions including logging services. It also features Castle DynamicProxy a lightweight runtime proxy generator, and Castle DictionaryAdapter.

Bunyan

Bunyan

It is a simple and fast JSON logging module for node.js services. It has extensible streams system for controlling where log records go (to a stream, to a file, log file rotation, etc.)

Fluent Bit

Fluent Bit

It is a super fast, lightweight, and highly scalable logging and metrics processor and forwarder. It is the preferred choice for cloud and containerized environments.

uno

uno

We built uno, a small tool similar to uniq (the UNIX CLI tool that removes duplicates) - but with fuzziness. uno considers two lines to be equal if their edit distance is less than a specified threshold, by default set to 30%. It reads from stdin and prints the deduplicated lines to stdout.

Zap

Zap

Zap takes a different approach. It includes a reflection-free, zero-allocation JSON encoder, and the base Logger strives to avoid serialization overhead and allocations wherever possible. By building the high-level SugaredLogger on that foundation, zap lets users choose when they need to count every allocation and when they'd prefer a more familiar, loosely typed API.

NanoLog

NanoLog

It is an extremely performant nanosecond scale logging system for C++ that exposes a simple printf-like API and achieves over 80 million logs/second at a median latency of just over 7 nanoseconds.

LogDevice

LogDevice

LogDevice is a scalable and fault tolerant distributed log system. While a file-system stores and serves data organized as files, a log system stores and delivers data organized as logs. The log can be viewed as a record-oriented, append-only, and trimmable file.

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