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Apache Spark VS Presto DB

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

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Apache Spark logo Apache Spark

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

Presto DB logo Presto DB

Distributed SQL Query Engine for Big Data (by Facebook)
  • Apache Spark Landing page
    Landing page //
    2021-12-31
  • Presto DB Landing page
    Landing page //
    2023-03-18

Apache Spark features and specs

  • Speed
    Apache Spark processes data in-memory, significantly increasing the processing speed of data tasks compared to traditional disk-based engines.
  • Ease of Use
    Spark offers high-level APIs in Java, Scala, Python, and R, making it accessible to a broad range of developers and data scientists.
  • Advanced Analytics
    Spark supports advanced analytics, including machine learning, graph processing, and real-time streaming, which can be executed in the same application.
  • Scalability
    Spark can handle both small- and large-scale data processing tasks, scaling seamlessly from a single machine to thousands of servers.
  • Support for Various Data Sources
    Spark can integrate with a wide variety of data sources, including HDFS, Apache HBase, Apache Hive, Cassandra, and many others.
  • Active Community
    Spark has a vibrant and active community, providing a wealth of extensions, tools, and support options.

Possible disadvantages of Apache Spark

  • Memory Consumption
    Spark's in-memory processing can be resource-intensive, requiring substantial amounts of RAM, which can drive up costs for large-scale deployments.
  • Complexity in Configuration
    To optimize performance, Spark requires careful configuration and tuning, which can be complex and time-consuming.
  • Learning Curve
    Despite its ease of use, mastering the full range of Spark's features and best practices can take considerable time and effort.
  • Latency for Small Data
    For smaller datasets or low-latency requirements, Spark might not be the most efficient choice, as other technologies could offer better performance.
  • Integration Overhead
    Though Spark integrates with many systems, incorporating it into an existing data infrastructure can introduce additional overhead and complexity.
  • Community Support Variability
    While the community is active, the support and quality of third-party libraries and tools can be inconsistent, leading to potential challenges in implementation.

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.

Apache Spark videos

+ Add

Weekly Apache Spark live Code Review -- look at StringIndexer multi-col (Scala) & Python testing

More videos:

  • Review - What's New in Apache Spark 3.0.0
  • Review - Apache Spark for Data Engineering and Analysis - Overview

Presto DB videos

No Presto DB videos yet. You could help us improve this page by suggesting one.

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Category Popularity

0-100% (relative to Apache Spark and Presto DB)

Apache Spark

Presto DB

Databases
86 86%
Databases
14% 14
Data Dashboard
0 0%
Data Dashboard
100% 100
Big Data
100 100%
Big Data
0% 0
Database Tools
0 0%
Database Tools
100% 100

User comments

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Reviews

These are some of the external sources and on-site user reviews we've used to compare Apache Spark and Presto DB

Apache Spark Reviews

15 data science tools to consider using in 2021
Apache Spark is an open source data processing and analytics engine that can handle large amounts of data -- upward of several petabytes, according to proponents. Spark's ability to rapidly process data has fueled significant growth in the use of the platform since it was created in 2009, helping to make the Spark project one of the largest open source communities among big...
Source: searchbusinessanalytics.techtarget.com
Top 15 Kafka Alternatives Popular In 2021
Apache Spark is a well-known, general-purpose, open-source analytics engine for large-scale, core data processing. It is known for its high-performance quality for data processing – batch and streaming with the help of its DAG scheduler, query optimizer, and engine. Data streams are processed in real-time and hence it is quite fast and efficient. Its machine learning...
Source: www.spec-india.com
5 Best-Performing Tools that Build Real-Time Data Pipeline
Apache Spark is an open-source and flexible in-memory framework which serves as an alternative to map-reduce for handling batch, real-time analytics and data processing workloads. It provides native bindings for the Java, Scala, Python, and R programming languages, and supports SQL, streaming data, machine learning and graph processing. From its beginning in the AMPLab at...
Source: www.analyticsinsight.net

Presto DB Reviews

We have no reviews of Presto DB yet.
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Social recommendations and mentions

Based on our record, Apache Spark should be more popular than Presto DB. It has been mentiond 70 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.

Apache Spark mentions (70)

  • Every Database Will Support Iceberg — Here's Why
    Apache Iceberg defines a table format that separates how data is stored from how data is queried. Any engine that implements the Iceberg integration — Spark, Flink, Trino, DuckDB, Snowflake, RisingWave — can read and/or write Iceberg data directly. - Source: dev.to / 14 days ago
  • How to Reduce Big Data Analytics Costs by 90% with Karpenter and Spark
    Apache Spark powers large-scale data analytics and machine learning, but as workloads grow exponentially, traditional static resource allocation leads to 30–50% resource waste due to idle Executors and suboptimal instance selection. - Source: dev.to / 16 days ago
  • Unveiling the Apache License 2.0: A Deep Dive into Open Source Freedom
    One of the key attributes of Apache License 2.0 is its flexible nature. Permitting use in both proprietary and open source environments, it has become the go-to choice for innovative projects ranging from the Apache HTTP Server to large-scale initiatives like Apache Spark and Hadoop. This flexibility is not solely legal; it is also philosophical. The license is designed to encourage transparency and maintain a... - Source: dev.to / about 2 months ago
  • The Application of Java Programming In Data Analysis and Artificial Intelligence
    [1] S. Russell and P. Norvig, Artificial Intelligence: A Modern Approach. Pearson, 2020. [2] F. Chollet, Deep Learning with Python. Manning Publications, 2018. [3] C. C. Aggarwal, Data Mining: The Textbook. Springer, 2015. [4] J. Dean and S. Ghemawat, "MapReduce: Simplified Data Processing on Large Clusters," Communications of the ACM, vol. 51, no. 1, pp. 107-113, 2008. [5] Apache Software Foundation, "Apache... - Source: dev.to / about 2 months ago
  • Automating Enhanced Due Diligence in Regulated Applications
    If you're designing an event-based pipeline, you can use a data streaming tool like Kafka to process data as it's collected by the pipeline. For a setup that already has data stored, you can use tools like Apache Spark to batch process and clean it before moving ahead with the pipeline. - Source: dev.to / 3 months ago
View more

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 / 11 days 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 / 12 days 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 / 26 days 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 / 4 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 / almost 3 years ago
View more

What are some alternatives?

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

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

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.

Hadoop - Open-source software for reliable, scalable, distributed computing

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

Apache Hive - Apache Hive data warehouse software facilitates querying and managing large datasets residing in distributed storage.

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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