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Presto DB VS Scalding

Compare Presto DB VS Scalding and see what are their differences

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Presto DB logo Presto DB

Distributed SQL Query Engine for Big Data (by Facebook)

Scalding logo Scalding

A Scala API for Cascading
  • Presto DB Landing page
    Landing page //
    2023-03-18
  • Scalding Landing page
    Landing page //
    2023-10-14

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.

Scalding features and specs

  • High-level Abstraction
    Scalding provides a more intuitive and higher-level abstraction over Hadoop's MapReduce, allowing developers to write concise Scala code instead of complex Java code.
  • Leverages Scala
    Being built in Scala, it allows users to take advantage of Scala’s functional programming features and its rich type system, which can lead to more efficient and expressive code.
  • Twitter Support
    Developed by Twitter, Scalding is used in production, ensuring that it receives the support and updates needed to handle large-scale data processing tasks effectively.
  • Integration with Hadoop
    Scalding is built on top of Cascading and integrates seamlessly with Hadoop, making it relatively straightforward to work with existing Hadoop infrastructure.
  • Support for Complex Workflows
    It provides mechanisms to build complex data processing workflows easily, handling features like joins and boilerplate reduction more gracefully compared to pure MapReduce.

Possible disadvantages of Scalding

  • Learning Curve
    Developers need to learn both Scala and the functional programming paradigm to use Scalding effectively, which can be challenging for those used to more traditional programming languages.
  • Scala Dependency
    The dependency on Scala can be a drawback for teams that do not already have Scala developers or are primarily Java/Python based, adding to hiring or training costs.
  • Performance Overhead
    Although Scalding abstracts a lot of the complexities of MapReduce, this abstraction can sometimes introduce performance overhead compared to finely-tuned native Hadoop jobs.
  • Community Size
    The community around Scalding is not as large as some other data processing frameworks, which could mean less community support and fewer third-party resources.
  • Evolving Ecosystem
    With the advent of newer big data processing frameworks like Apache Spark, Scalding has seen reduced prominence in the big data ecosystem, which could impact its longevity and support in the future.

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.

Category Popularity

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

Presto DB

Scalding

Data Dashboard
84 84%
Data Dashboard
16% 16
Database Tools
84 84%
Database Tools
16% 16
Big Data Analytics
81 81%
Big Data Analytics
19% 19
Databases
100 100%
Databases
0% 0

User comments

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Social recommendations and mentions

Based on our record, Presto DB seems to be more popular. It has been mentiond 10 times since March 2021. 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.

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
View more

Scalding mentions (0)

We have not tracked any mentions of Scalding yet. Tracking of Scalding recommendations started around Mar 2021.

What are some alternatives?

When comparing Presto DB and Scalding, 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.

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

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.

Databricks - Databricks provides a Unified Analytics Platform that accelerates innovation by unifying data science, engineering and business.‎What is Apache Spark?

Rakam - Custom analytics platform

Informatica - As the world’s leader in enterprise cloud data management, we’re prepared to help you intelligently lead—in any sector, category or niche.

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