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GraphQL VS Presto DB

Compare GraphQL VS Presto DB and see what are their differences

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GraphQL logo GraphQL

GraphQL is a data query language and runtime to request and deliver data to mobile and web apps.

Presto DB logo Presto DB

Distributed SQL Query Engine for Big Data (by Facebook)
  • GraphQL Landing page
    Landing page //
    2023-08-01
  • Presto DB Landing page
    Landing page //
    2023-03-18

GraphQL features and specs

  • Efficient Data Retrieval
    GraphQL allows clients to request only the data they need, reducing the amount of data transferred over the network and improving performance.
  • Strongly Typed Schema
    GraphQL uses a strongly typed schema to define the capabilities of an API, providing clear and explicit API contracts and enabling better tooling support.
  • Single Endpoint
    GraphQL operates through a single endpoint, unlike REST APIs which require multiple endpoints. This simplifies the server architecture and makes it easier to manage.
  • Introspection
    GraphQL allows clients to query the schema for details about the available types and operations, which facilitates the development of powerful developer tools and IDE integrations.
  • Declarative Data Fetching
    Clients can specify the shape of the response data declaratively, which enhances flexibility and ensures that the client and server logic are decoupled.
  • Versionless
    Because clients specify exactly what data they need, there is no need to create different versions of an API when making changes. This helps in maintaining backward compatibility.
  • Increased Responsiveness
    GraphQL can batch multiple requests into a single query, reducing the latency and improving the responsiveness of applications.

Possible disadvantages of GraphQL

  • Complexity
    The setup and maintenance of a GraphQL server can be complex. Developers need to define the schema precisely and handle resolvers, which can be more complicated than designing REST endpoints.
  • Over-fetching Risk
    Though designed to mitigate over-fetching, poorly designed GraphQL queries can lead to the server needing to fetch more data than necessary, causing performance issues.
  • Caching Challenges
    Caching in GraphQL is more challenging than in REST, since different queries can change the shape and size of the response data, making traditional caching mechanisms less effective.
  • Learning Curve
    GraphQL has a steeper learning curve compared to RESTful APIs because it introduces new concepts such as schemas, types, and resolvers which developers need to understand thoroughly.
  • Complex Rate Limiting
    Implementing rate limiting is more complex with GraphQL than with REST. Since a single query can potentially request a large amount of data, simple per-endpoint rate limiting strategies are not effective.
  • Security Risks
    GraphQL's flexibility can introduce security risks. For example, improperly managed schemas could expose sensitive information, and complex queries can lead to denial-of-service attacks.
  • Overhead on Small Applications
    For smaller applications with simpler use cases, the overhead introduced by setting up and maintaining a GraphQL server may not be justified compared to a straightforward REST API.

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 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.

GraphQL videos

+ Add

REST vs. GraphQL: Critical Look

More videos:

  • Review - REST vs GraphQL - What's the best kind of API?
  • Review - What Is GraphQL?

Presto DB videos

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Category Popularity

0-100% (relative to GraphQL and Presto DB)

GraphQL

Presto DB

Developer Tools
100 100%
Developer Tools
0% 0
Data Dashboard
0 0%
Data Dashboard
100% 100
JavaScript Framework
100 100%
JavaScript Framework
0% 0
Database Tools
0 0%
Database Tools
100% 100

User comments

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Social recommendations and mentions

Based on our record, GraphQL seems to be a lot more popular than Presto DB. While we know about 247 links to GraphQL, we've tracked only 10 mentions of 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.

GraphQL mentions (247)

  • From REST to GraphQL: My First Impressions and Setup Experience
    Recently, I started exploring GraphQL while working on my MERN stack project. I learnt this through some youtube videos and some Other sources. Https://graphql.org/. - Source: dev.to / 13 days ago
  • Top 10 Programming Trends and Languages to Watch in 2025
    Sonja Keerl, CTO of MACH Alliance, states, "Composable architectures enable enterprises to innovate faster by assembling best-in-class solutions." Developers must embrace technologies like GraphQL, gRPC, and OpenAPI to remain competitive. - Source: dev.to / 25 days ago
  • 🚀 REST API vs. GraphQL: Which One Should You Use in 2025?
    📌 Learn more about GraphQL: https://graphql.org/. - Source: dev.to / 3 months ago
  • Next.js vs Nest.js: What to Choose in 2025?
    Nest.js has been most widely adopted in developing back-end applications such as RESTful APIs, GraphQL services, and microservices. With its modular design, this framework is well and truly set for large project management; it allows for smooth and efficient performance through built-in features such as dependency injection and strong middleware support. - Source: dev.to / 4 months ago
  • The Power of GraphQL: A Beginner’s Guide to Modern Web Development
    Overview: Managing data efficiently is crucial for delivering smooth user experiences in today's fast-paced digital world. One technology that has revolutionized data handling in web development is GraphQL. This query language for APIs has transformed the way developers interact with data sources, offering flexibility, efficiency, and speed. - Source: dev.to / 4 months 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 1 month 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 1 month 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 / about 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 GraphQL and Presto DB, you can also consider the following products

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

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.

React - A JavaScript library for building user interfaces

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

Next.js - A small framework for server-rendered universal JavaScript apps

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.

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