Software Alternatives, Accelerators & Startups

Apache Ambari VS Protocol Buffers

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

Note: These products don't have any matching categories. If you think this is a mistake, please edit the details of one of the products and suggest appropriate categories.

Apache Ambari logo Apache Ambari

Ambari is aimed at making Hadoop management simpler by developing software for provisioning, managing, and monitoring Hadoop clusters.

Protocol Buffers logo Protocol Buffers

A method for serializing and interchanging structured data.
  • Apache Ambari Landing page
    Landing page //
    2023-01-08
  • Protocol Buffers Landing page
    Landing page //
    2023-08-02

Apache Ambari features and specs

  • Centralized Management
    Apache Ambari provides a centralized platform to manage, monitor, and provision Hadoop clusters efficiently. This feature simplifies the administration tasks by offering a single interface for managing cluster operations.
  • User-Friendly Interface
    Ambari offers a graphical user interface (GUI) that is intuitive and easy to use, enabling administrators to manage clusters without requiring extensive command-line knowledge.
  • Automated Installation
    It supports automated installation and configuration of Hadoop components, reducing the complexity and time required to set up a cluster.
  • Real-time Monitoring
    Ambari provides real-time insights into cluster health and performance through a variety of metrics and dashboards, allowing for proactive management.
  • Extensibility
    The platform is designed to be extensible, allowing developers to write custom alerts and metrics, thus adapting the system to meet specific needs.

Possible disadvantages of Apache Ambari

  • Resource Intensive
    Ambari can consume significant system resources, especially in larger clusters, which could impact performance if resources are not adequately provisioned.
  • Limited Support for Non-Hadoop Ecosystems
    The primary focus of Apache Ambari is on Hadoop ecosystems, and it lacks extensive support for non-Hadoop big data technologies, which can limit its applicability in heterogeneous environments.
  • Complexity for Small Clusters
    For smaller Hadoop deployments, the use of Ambari might be overkill and add unnecessary complexity due to its comprehensive nature.
  • Dependency on Updates
    Users can encounter compatibility issues or bugs following updates, which can require troubleshooting and delay important operations.
  • Steep Learning Curve for Customization
    While it is extensible, customization in Ambari can have a steep learning curve, demanding deeper technical knowledge to implement specific configurations or custom components.

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 Ambari videos

No Apache Ambari videos yet. You could help us improve this page by suggesting one.

Add video

Protocol Buffers videos

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 Ambari and Protocol Buffers)
Data Dashboard
100 100%
0% 0
Configuration Management
0 0%
100% 100
Development
100 100%
0% 0
Web Servers
0 0%
100% 100

User comments

Share your experience with using Apache Ambari and Protocol Buffers. For example, how are they different and which one is better?
Log in or Post with

Social recommendations and mentions

Based on our record, Protocol Buffers seems to be a lot more popular than Apache Ambari. While we know about 23 links to Protocol Buffers, we've tracked only 1 mention of Apache Ambari. 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 Ambari mentions (1)

  • In One Minute : Hadoop
    Ambari, A web-based tool for provisioning, managing, and monitoring Apache Hadoop clusters which includes support for Hadoop HDFS, Hadoop MapReduce, Hive, HCatalog, HBase, ZooKeeper, Oozie, Pig and Sqoop. Ambari also provides a dashboard for viewing cluster health such as heatmaps and ability to view MapReduce, Pig and Hive applications visually along with features to diagnose their performance characteristics in... - Source: dev.to / over 2 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 Ambari and Protocol Buffers, you can also consider the following products

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

TOML - TOML - Tom's Obvious, Minimal Language

Apache HBase - Apache HBase – Apache HBase™ Home

Messagepack - An efficient binary serialization format.

Apache Mahout - Distributed Linear Algebra

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