Software Alternatives & Reviews

Presto DB VS Apache Flink

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

Presto DB logo Presto DB

Distributed SQL Query Engine for Big Data (by Facebook)

Apache Flink logo Apache Flink

Flink is a streaming dataflow engine that provides data distribution, communication, and fault tolerance for distributed computations.
  • Presto DB Landing page
    Landing page //
    2023-03-18
  • Apache Flink Landing page
    Landing page //
    2023-10-03

Presto DB videos

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Apache Flink videos

GOTO 2019 • Introduction to Stateful Stream Processing with Apache Flink • Robert Metzger

More videos:

  • Tutorial - Apache Flink Tutorial | Flink vs Spark | Real Time Analytics Using Flink | Apache Flink Training
  • Tutorial - How to build a modern stream processor: The science behind Apache Flink - Stefan Richter

Category Popularity

0-100% (relative to Presto DB and Apache Flink)
Data Dashboard
100 100%
0% 0
Big Data
0 0%
100% 100
Database Tools
100 100%
0% 0
Stream Processing
0 0%
100% 100

User comments

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Social recommendations and mentions

Based on our record, Apache Flink should be more popular than Presto DB. It has been mentiond 27 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 (6)

  • 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 2 years ago
  • Can a data warehouse be skipped?
    Fair point, but I am talking about Athena (not SQL Server), which under the hood uses a distributed query engine. It is capable to deal with huge amounts of data, if the storage is in the right shape. You can read more about the underlying technology here: https://prestodb.io/. Source: about 2 years ago
  • why use Redshift if we can use S3 to store data and can connect with Quicksight for dashboarding?
    So there is Presto, which is a distributed SQL engine created by Facebook. Source: about 2 years ago
  • Understanding AWS Athena 101
    You can use Athena to run data analytics, with just standard SQL (Presto). - Source: dev.to / over 2 years ago
  • ETL tool for query building across multiple databases in Mongo DB
    Presto does this, but I'm honestly uncertain how performant it is. In my experience, centralizing data is the superior approach to attempting to query multiple sources in place. Source: almost 3 years ago
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Apache Flink mentions (27)

  • Top 10 Common Data Engineers and Scientists Pain Points in 2024
    Data scientists often prefer Python for its simplicity and powerful libraries like Pandas or SciPy. However, many real-time data processing tools are Java-based. Take the example of Kafka, Flink, or Spark streaming. While these tools have their Python API/wrapper libraries, they introduce increased latency, and data scientists need to manage dependencies for both Python and JVM environments. For example,... - Source: dev.to / 22 days ago
  • Choosing Between a Streaming Database and a Stream Processing Framework in Python
    Other stream processing engines (such as Flink and Spark Streaming) provide SQL interfaces too, but the key difference is a streaming database has its storage. Stream processing engines require a dedicated database to store input and output data. On the other hand, streaming databases utilize cloud-native storage to maintain materialized views and states, allowing data replication and independent storage scaling. - Source: dev.to / 3 months ago
  • Go concurrency simplified. Part 4: Post office as a data pipeline
    Also, this knowledge applies to learning more about data engineering, as this field of software engineering relies heavily on the event-driven approach via tools like Spark, Flink, Kafka, etc. - Source: dev.to / 4 months ago
  • Five Apache projects you probably didn't know about
    Apache SeaTunnel is a data integration platform that offers the three pillars of data pipelines: sources, transforms, and sinks. It offers an abstract API over three possible engines: the Zeta engine from SeaTunnel or a wrapper around Apache Spark or Apache Flink. Be careful, as each engine comes with its own set of features. - Source: dev.to / 5 months ago
  • Getting Started with Flink SQL, Apache Iceberg and DynamoDB Catalog
    Due to the technology transformation we want to do recently, we started to investigate Apache Iceberg. In addition, the data processing engine we use in house is Apache Flink, so it's only fair to look for an experimental environment that integrates Flink and Iceberg. - Source: dev.to / 5 months ago
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What are some alternatives?

When comparing Presto DB and Apache Flink, 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.

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

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

Amazon Kinesis - Amazon Kinesis services make it easy to work with real-time streaming data in the AWS cloud.

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.

Spring Framework - The Spring Framework provides a comprehensive programming and configuration model for modern Java-based enterprise applications - on any kind of deployment platform.