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Apache Pig VS Protocol Buffers

Compare Apache Pig VS Protocol Buffers and see what are their differences

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  2. » Videos
  3. » Reviews
  4. » Alternatives

Apache Pig logo Apache Pig

Pig is a high-level platform for creating MapReduce programs used with Hadoop.

Protocol Buffers logo Protocol Buffers

A method for serializing and interchanging structured data.
  • Apache Pig Landing page
    Landing page //
    2021-12-31
  • Protocol Buffers Landing page
    Landing page //
    2023-08-02

Apache Pig features and specs

  • Simplicity
    Apache Pig provides a high-level scripting language called Pig Latin that is much easier to write and understand than complex MapReduce code, enabling faster development time.
  • Abstracts Hadoop Complexity
    Pig abstracts the complexity of Hadoop, allowing developers to focus on data processing rather than worrying about the intricacies of Hadoop’s underlying mechanisms.
  • Extensibility
    Pig allows user-defined functions (UDFs) to process various types of data, giving users the flexibility to extend its functionality according to their specific requirements.
  • Optimized Query Execution
    Pig includes a rich set of optimization techniques that automatically optimize the execution of scripts, thereby improving performance without needing manual tuning.
  • Error Handling and Debugging
    The platform has an extensive error handling mechanism and provides the ability to make debugging easier through logging and stack traces, making it simpler to troubleshoot issues.

Possible disadvantages of Apache Pig

  • Performance Limitations
    While Pig simplifies writing MapReduce operations, it may not always offer the same level of performance as hand-optimized, low-level MapReduce code.
  • Limited Real-Time Processing
    Pig is primarily designed for batch processing and may not be the best choice for real-time data processing requirements.
  • Steeper Learning Curve for SQL Users
    Developers who are already familiar with SQL might find Pig Latin to be less intuitive at first, resulting in a steeper learning curve for building complex data transformations.
  • Maintenance Overhead
    As Pig scripts grow in complexity and number, maintaining and managing these scripts can become challenging, particularly in large-scale production environments.
  • Growing Obsolescence
    With the rise of more versatile and performant Big Data tools like Apache Spark and Hive, Pig’s relevance and community support have been on the decline.

Protocol Buffers features and specs

  • Efficiency
    Protocol Buffers are designed to be compact and efficient, using less space compared to other serialization formats like XML or JSON. This efficiency benefits both storage and network transmission.
  • Backward and Forward Compatibility
    Protocol Buffers support easy schema evolution. New fields can be added to your protocol without breaking existing deployed programs that are compiled with an older version of the protocol.
  • Performance
    They offer fast serialization and deserialization, which can significantly improve performance in applications where speed is critical.
  • Language Support
    Protocol Buffers are supported in multiple programming languages, making them flexible for use in diverse tech stacks and across different systems.
  • Type Safety
    With Protocol Buffers, schemas are strictly defined, which provides a level of type safety compared to text-based formats like JSON or XML.

Possible disadvantages of Protocol Buffers

  • Learning Curve
    The initial setup and understanding of Protocol Buffers can be complex for those who are not familiar with binary serialization formats.
  • Debugging Difficulty
    Because Protocol Buffers use a compact and binary format, debugging can be more challenging compared to human-readable formats like JSON or XML.
  • Limited Human Readability
    As a binary format, Protocol Buffers are not easily readable without decoding, which can complicate manual inspection of data during development or troubleshooting.
  • Third-Party Dependency
    Using Protocol Buffers often requires integrating additional libraries into your project, which can introduce dependencies that need to be maintained.
  • Tooling Overhead
    The use of Protocol Buffers requires a compilation step and the generation of code from .proto files, which adds complexity and build-time overhead.

Apache Pig videos

+ Add

Pig Tutorial | Apache Pig Script | Hadoop Pig Tutorial | Edureka

More videos:

  • Review - Simple Data Analysis with Apache Pig

Protocol Buffers videos

+ Add

Protocol Buffers- A Banked Journey - Christopher Reeves

More videos:

  • Review - justforfunc #30: The Basics of Protocol Buffers
  • Review - Complete Introduction to Protocol Buffers 3 : How are Protocol Buffers used?

Category Popularity

0-100% (relative to Apache Pig and Protocol Buffers)

Apache Pig

Protocol Buffers

Data Dashboard
100 100%
Data Dashboard
0% 0
Configuration Management
0 0%
Configuration Management
100% 100
Database Tools
100 100%
Database Tools
0% 0
Web Servers
0 0%
Web Servers
100% 100

User comments

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Social recommendations and mentions

Based on our record, Protocol Buffers seems to be a lot more popular than Apache Pig. While we know about 23 links to Protocol Buffers, we've tracked only 2 mentions of Apache Pig. We are tracking product recommendations and mentions on various public social media platforms and blogs. They can help you identify which product is more popular and what people think of it.

Apache Pig mentions (2)

  • In One Minute : Hadoop
    Pig, a platform/programming language for authoring parallelizable jobs. - Source: dev.to / over 2 years ago
  • Spark is lit once again
    In the early days of the Big Data era when K8s hasn't even been born yet, the common open source go-to solution was the Hadoop stack. We have written several old-fashioned Map-Reduce jobs, scripts using Pig until we came across Spark. Since then Spark has became one of the most popular data processing engines. It is very easy to start using Lighter on YARN deployments. Just run a docker with proper configuration... - Source: dev.to / over 3 years ago

Protocol Buffers mentions (23)

  • Pulumi Gestalt 0.0.1 released
    A schema.json converter for easier ingestion (likely supporting Avro and Protobuf). - Source: dev.to / about 2 months ago
  • Understanding Protocol Buffers: A Fast Alternative to JSON
    Protocol Buffers Documentation Protobuf Json JSON in API Development. - Source: dev.to / 5 months ago
  • gRPC: what is it? An introduction...
    For our luck, Go is one of the 11 languages with official libraries. It is important to say that the framework uses Protocol Buffer to serialize the message. The first step then is to install locally the protobuf and its Go plugins:. - Source: dev.to / 7 months ago
  • Why should we use Protobuf in Web API as data transfer protocol.
    Note: Clients and services will ignore field numbers they do not recognize. For more details about Protobuf, visit protobuf.dev. - Source: dev.to / 8 months ago
  • JSON vs FlatBuffers vs Protocol Buffers
    Protobuf (Protocol Buffers), created by Google, is, according to the official website :. - Source: dev.to / 9 months ago
View more

What are some alternatives?

When comparing Apache Pig and Protocol Buffers, you can also consider the following products

Looker - Looker makes it easy for analysts to create and curate custom data experiences—so everyone in the business can explore the data that matters to them, in the context that makes it truly meaningful.

TOML - TOML - Tom's Obvious, Minimal Language

Jupyter - Project Jupyter exists to develop open-source software, open-standards, and services for interactive computing across dozens of programming languages. Ready to get started? Try it in your browser Install the Notebook.

Messagepack - An efficient binary serialization format.

Presto DB - Distributed SQL Query Engine for Big Data (by Facebook)

gRPC - Application and Data, Languages & Frameworks, Remote Procedure Call (RPC), and Service Discovery

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