Software Alternatives, Accelerators & Startups
Register | Login

Apache Thrift VS Apache Avro

Compare Apache Thrift VS Apache Avro and see what are their differences

Draxlr
Turn SQL Data into Decisions. Build professional dashboards and data visualizations without technical expertise. Easily embed analytics anywhere, receive automated alerts, and discover AI-powered insights all through a straightforward interface. featured
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.
Contents:
  1. » Base Details
  2. » Videos
  3. » Reviews
  4. » Alternatives

Apache Thrift logo Apache Thrift

An interface definition language and communication protocol for creating cross-language services.

Apache Avro logo Apache Avro

Apache Avro is a comprehensive data serialization system and acting as a source of data exchanger service for Apache Hadoop.
  • Apache Thrift Landing page
    Landing page //
    2019-07-12
  • Apache Avro Landing page
    Landing page //
    2022-10-21

Apache Thrift features and specs

  • Cross-Language Support
    Apache Thrift supports numerous programming languages including Java, Python, C++, Ruby, and more, enabling seamless communication between services written in different languages.
  • Efficient Serialization
    Thrift offers efficient binary serialization which helps in reducing the payload size and improves the communication speed between services.
  • Service Definition Flexibility
    Thrift provides a robust interface definition language (IDL) for defining and generating code for services with strict type checking, fostering strong contract interfaces.
  • Scalability
    Due to its lightweight and efficient serialization mechanisms, Apache Thrift can handle a large number of simultaneous client connections, making it suitable for scalable distributed systems.
  • Versioning Support
    Thrift supports service versioning which helps in evolving APIs without disrupting existing services or clients.

Possible disadvantages of Apache Thrift

  • Steep Learning Curve
    For new users, especially those not familiar with RPC frameworks, learning and understanding Thrift’s IDL and operations can be complex and time-consuming.
  • Documentation and Community Support
    Compared to some alternative technologies, Apache Thrift's documentation and community support can be less robust, which might pose challenges in troubleshooting or seeking guidance.
  • Lack of Advanced Features
    Thrift does not support some advanced features like streaming or multiplexing out of the box, which could limit its use in complex systems requiring these functionalities.
  • Infrastructure Overhead
    Integrating Thrift into an existing system might introduce infrastructure overhead both in initial setup and ongoing maintenance, especially when dealing with multiple languages.
  • Protocol Limitations
    While Thrift is highly efficient, its protocol limitations might require additional workarounds for certain data structures or transport mechanisms, complicating development.

Apache Avro features and specs

  • Schema Evolution
    Avro supports seamless schema evolution, allowing you to add fields and change data types without impacting existing data. This flexibility is advantageous in environments where data structures frequently change.
  • Compact Binary Format
    Avro uses a compact binary format for data serialization, leading to efficient storage and faster data transmission compared to text-based formats like JSON or XML.
  • Language Agnostic
    Avro is designed to be language agnostic, with support for multiple programming languages, including Java, Python, C++, and more. This makes it easier to integrate with various systems.
  • No Code Generation Required
    Unlike other serialization frameworks such as Protocol Buffers and Thrift, Avro does not require generating code from the schema, simplifying the development process.
  • Self Describing
    Each Avro data file contains its schema, making the data self-describing. This helps maintain consistency between data producers and consumers.

Possible disadvantages of Apache Avro

  • Lack of Human Readability
    Avro's binary format is not human-readable, making it challenging to debug or inspect data without specialized tools.
  • Schema Management Overhead
    While Avro supports schema evolution, managing and maintaining these schemas across multiple services can become complex and require additional coordination.
  • Limited Support for Complex Data Types
    Avro has limitations when it comes to the representation of certain complex data types, which might necessitate workarounds or transformations that add complexity.
  • Learning Curve
    Users who are new to Apache Avro may face a learning curve to understand schema creation, evolution, and integration within their data pipelines.
  • Dependency on Schema Registry
    Using Avro effectively often requires integrating with a schema registry, adding an extra layer of infrastructure and potential points of failure.

Apache Thrift videos

+ Add

Apache Thrift

Apache Avro videos

+ Add

CCA 175 : Apache Avro Introduction

More videos:

  • Review - End to end Data Governance with Apache Avro and Atlas

Category Popularity

0-100% (relative to Apache Thrift and Apache Avro)

Apache Thrift

Apache Avro

Web Servers
100 100%
Web Servers
0% 0
Development
0 0%
Development
100% 100
Web And Application Servers
100 100%
Web And Application Servers
0% 0
Data Dashboard
0 0%
Data Dashboard
100% 100

User comments

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

Social recommendations and mentions

Apache Avro might be a bit more popular than Apache Thrift. We know about 14 links to it since March 2021 and only 13 links to Apache Thrift. 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 Thrift mentions (13)

  • Show HN: TypeSchema – A JSON specification to describe data models
    I once read a paper about Apache/Meta Thrift [1,2]. It allows you to define data types/interfaces in a definition file and generate code for many programming languages. It was specifically designed for RPCs and microservices. [1]: https://thrift.apache.org/. - Source: Hacker News / 6 months ago
  • Delving Deeper: Enriching Microservices with Golang with CloudWeGo
    While gRPC and Apache Thrift have served the microservice architecture well, CloudWeGo's advanced features and performance metrics set it apart as a promising open source solution for the future. - Source: dev.to / about 1 year ago
  • Reddit System Design/Architecture
    Services in general communicate via Thrift (and in some cases HTTP). Source: about 2 years ago
  • Universal type language!
    Protocol Buffers is the most popular one, but there are many others such as Apache Thrift and my own Typical. Source: about 2 years ago
  • You worked on it? Why is it slow then?
    RPC is not strictly OO, but you can think of RPC calls like method calls. In general it will reflect your interface design and doesn't have to be top-down, although a good project usually will look that way. A good contrast to REST where you use POST/PUT/GET/DELETE pattern on resources where as a procedure call could be a lot more flexible and potentially lighter weight. Think of it like defining methods in code... Source: over 2 years ago
View more

Apache Avro mentions (14)

  • 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
  • Why Data Security is Broken and How to Fix it?
    Security Aware Data Metadata Data schema formats such as Avro and Json currently lack built-in support for data sensitivity or security-aware metadata. Additionally, common formats like Parquet and Iceberg, while efficient for storing large datasets, don’t natively include security-aware metadata. At Jarrid, we are exploring various metadata formats to incorporate data sensitivity and security-aware attributes... - Source: dev.to / 7 months ago
  • Open Table Formats Such as Apache Iceberg Are Inevitable for Analytical Data
    Apache AVRO [1] is one but it has been largely replaced by Parquet [2] which is a hybrid row/columnar format [1] https://avro.apache.org/. - Source: Hacker News / over 1 year ago
  • Generating Avro Schemas from Go types
    The most common format for describing schema in this scenario is Apache Avro. - Source: dev.to / over 1 year ago
  • gRPC on the client side
    Other serialization alternatives have a schema validation option: e.g., Avro, Kryo and Protocol Buffers. Interestingly enough, gRPC uses Protobuf to offer RPC across distributed components:. - Source: dev.to / about 2 years ago
View more

What are some alternatives?

When comparing Apache Thrift and Apache Avro, you can also consider the following products

Docker Hub - Docker Hub is a cloud-based registry service

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

Eureka - Eureka is a contact center and enterprise performance through speech analytics that immediately reveals insights from automated analysis of communications including calls, chat, email, texts, social media, surveys and more.

Apache HBase - Apache HBase – Apache HBase™ Home

Traefik - Load Balancer / Reverse Proxy

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

Loading...