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Presto DB VS Spring Batch

Compare Presto DB VS Spring Batch and see what are their differences

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Presto DB logo Presto DB

Distributed SQL Query Engine for Big Data (by Facebook)

Spring Batch logo Spring Batch

Level up your Java code and explore what Spring can do for you.
  • Presto DB Landing page
    Landing page //
    2023-03-18
  • Spring Batch Landing page
    Landing page //
    2023-08-26

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.

Spring Batch features and specs

  • Robust Framework
    Spring Batch is a mature and robust framework that has been widely adopted in the industry for batch processing, offering a comprehensive set of features and a high level of reliability.
  • Integration with Spring
    Tightly integrated with the Spring ecosystem, making it easy to leverage other Spring modules and features, such as dependency injection, for batch applications.
  • Scalability
    Supports both parallel and distributed processing, allowing for scalable batch processing solutions that can handle large volumes of data efficiently.
  • Transaction Management
    Provides robust transaction management, ensuring data consistency and integrity during batch processing.
  • Comprehensive Error Handling
    Offers detailed error handling and retry mechanisms, which help in managing exceptions and ensuring that batch jobs can recover gracefully from failures.
  • Strong Community Support
    Backed by a strong community and excellent documentation, which can help developers overcome challenges and optimize their batch processing solutions.

Possible disadvantages of Spring Batch

  • Steep Learning Curve
    The framework's extensive features and configurations can result in a steep learning curve for new users, especially those unfamiliar with the Spring ecosystem.
  • Complex Configuration
    Configuring batch jobs can be complex and may require significant setup, particularly for users unfamiliar with XML or Spring configuration.
  • Verbose Code
    Spring Batch can lead to verbose code, as developers need to define many components and configurations, which can make maintenance more challenging.
  • Overhead for Small Jobs
    For simple batch tasks, using Spring Batch may introduce unnecessary complexity and overhead, as the framework is designed for more complex and large-scale batch processing.

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.

Presto DB videos

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Spring Batch videos

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Spring Batch Scheduling

More videos:

  • Review - ETE 2012 - Josh Long - Behind the Scenes of Spring Batch

Category Popularity

0-100% (relative to Presto DB and Spring Batch)

Presto DB

Spring Batch

Data Dashboard
100 100%
Data Dashboard
0% 0
Databases
58 58%
Databases
42% 42
Database Tools
100 100%
Database Tools
0% 0
Big Data
0 0%
Big Data
100% 100

User comments

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Social recommendations and mentions

Based on our record, Presto DB should be more popular than Spring Batch. 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 / 5 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 / 5 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 / 6 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 / 9 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 / over 3 years ago
View more

Spring Batch mentions (2)

What are some alternatives?

When comparing Presto DB and Spring Batch, you can also consider the following products

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

Apache Spark - Apache Spark is an engine for big data processing, with built-in modules for streaming, SQL, machine learning and graph processing.

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.

ClickHouse - ClickHouse is an open-source column-oriented database management system that allows generating analytical data reports in real time.

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.

Apache Flink - Flink is a streaming dataflow engine that provides data distribution, communication, and fault tolerance for distributed computations.

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