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Apache Thrift VS Presto DB

Compare Apache Thrift VS Presto DB and see what are their differences

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Apache Thrift logo Apache Thrift

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

Presto DB logo Presto DB

Distributed SQL Query Engine for Big Data (by Facebook)
  • Apache Thrift Landing page
    Landing page //
    2019-07-12
  • Presto DB Landing page
    Landing page //
    2023-03-18

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.

Presto DB features and specs

  • High-Performance Query Engine
    Presto is designed for high-performance querying, capable of performing complex analytics and large-scale data processing at interactive speeds.
  • Distributed SQL Query Engine
    Presto can scale out to large clusters of machines, allowing for efficient distribution of queries over multiple servers to handle big data workloads.
  • Versatility
    Supports querying data from multiple data sources such as Hadoop, relational databases, NoSQL databases, and cloud object storage within a single query.
  • ANSI-SQL Compatibility
    Presto supports ANSI SQL, making it easier for users familiar with SQL to adapt and write queries without a steep learning curve.
  • Open Source
    Presto is an open-source project, which means it benefits from continuous community contributions and improvements, keeping it up-to-date and robust.
  • Extensible
    Presto's architecture is designed to be extensible, allowing users to add custom functions and connectors, tailored to specific needs.

Possible disadvantages of Presto DB

  • Resource Intensive
    High performance comes with significant resource requirements, necessitating robust infrastructure to realize its full potential.
  • Complex Configuration
    Setting up and configuring Presto can be complex and time-consuming, often requiring expertise and an understanding of its various components.
  • Limited Support for Transactions
    Presto is primarily designed for reading data and performing analytics, and it has limited support for transactional processing compared to traditional relational databases.
  • Community Support
    While it has a vibrant open-source community, users may find the support less comprehensive than that provided by commercial enterprise solutions.
  • Latency for Small Queries
    Designed for big data and complex queries, Presto may exhibit higher latency for small, simple queries compared to specialized databases optimized for such use cases.
  • Maintenance Overhead
    Managing and maintaining a Presto cluster can be labor-intensive, requiring ongoing tuning and maintenance to ensure optimal performance and reliability.

Analysis of Apache Thrift

Overall verdict

  • Yes, Apache Thrift is considered to be a good option for projects needing cross-language communication and efficient serialization. Its efficiency and wide adoption have proven it to be a reliable framework in many production environments.

Why this product is good

  • Apache Thrift is a widely used framework for scalable cross-language services development. It allows for seamless communication between programs written in different languages by providing code generation and serialization capabilities for a variety of languages. Thrift supports an efficient binary protocol and is highly customizable, making it a robust choice for services that require performance and flexibility. Additionally, it's an open-source project under the Apache Software Foundation, which ensures it has a strong community and ongoing updates.

Recommended for

  • Organizations that require cross-language service communication
  • Projects that need high-performance and low-latency data transmission
  • Developers looking for a framework with support for multiple programming languages
  • Teams looking for a customizable serialization protocol

Analysis of Presto DB

Overall verdict

  • PrestoDB is considered a strong choice for organizations needing to perform fast and complex analytic queries. Its ability to execute SQL queries on big data at lightning speeds makes it an attractive tool for data-driven organizations. However, the choice of PrestoDB depends on specific use cases, existing infrastructure, and the team's familiarity with its architecture and operational demands.

Why this product is good

  • PrestoDB is a highly-regarded distributed SQL query engine that excels in speed and efficiency for querying large datasets. It's designed for running interactive analytic queries against data sources of all sizes. Some of its core strengths include its ability to query data across a wide variety of sources, scalability, and strong community support. It's often chosen for its capability to integrate seamlessly in environments requiring fast data processing and analysis without the need to move or transform data extensively.

Recommended for

    PrestoDB is ideal for technology firms, data-driven companies, and organizations in need of real-time data analytics. It is especially well-suited for those with existing big data frameworks (like Hadoop, Kafka, and Cassandra) who require a performant query engine to leverage large datasets efficiently. It's recommended for teams familiar with distributed systems who need the flexibility and speed offered by PrestoDB's architecture.

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Category Popularity

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User comments

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Social recommendations and mentions

Apache Thrift might be a bit more popular than Presto DB. We know about 13 links to it since March 2021 and only 10 links to Presto DB. 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 / 8 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 / over 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: over 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
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Presto DB mentions (10)

  • Data Warehouses and Data Lakes: Understanding Modern Data Storage Paradigms 📦
    Follow Presto at Official Website, Linkedin, Youtube, and Slack channel to join the community. - Source: dev.to / about 2 months ago
  • Introduction to Presto: Open Source SQL Query Engine that's changing Big Data Analytics
    In today's data-driven world, organizations face a constant challenge: how to analyse massive datasets quickly and efficiently without moving data between disparate systems. Presto, an open-source distributed SQL query engine that's revolutionizing how we approach big data analytics. - Source: dev.to / about 2 months ago
  • Twitter's 600-Tweet Daily Limit Crisis: Soaring GCP Costs and the Open Source Fix Elon Musk Ignored
    Presto: Presto is an open-source distributed SQL query engine that enables querying data from various sources. It provides fast and interactive analytics capabilities, supporting a wide range of data formats and integration with different storage systems. - Source: dev.to / 2 months ago
  • Using IRIS and Presto for high-performance and scalable SQL queries
    The rise of Big Data projects, real-time self-service analytics, online query services, and social networks, among others, have enabled scenarios for massive and high-performance data queries. In response to this challenge, MPP (massively parallel processing database) technology was created, and it quickly established itself. Among the open-source MPP options, Presto (https://prestodb.io/) is the best-known... - Source: dev.to / 5 months ago
  • Parsing logs from multiple data sources with Ahana and Cube
    Presto is an open-source distributed SQL query engine, originally developed at Facebook, now hosted under the Linux Foundation. It connects to multiple databases or other data sources (for example, Amazon S3). We can use a Presto cluster as a single compute engine for an entire data lake. - Source: dev.to / about 3 years ago
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What are some alternatives?

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

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

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.

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.

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.

Traefik - Load Balancer / Reverse Proxy

Google BigQuery - A fully managed data warehouse for large-scale data analytics.

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