Software Alternatives & Reviews

Presto DB VS Apache Arrow

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

Presto DB logo Presto DB

Distributed SQL Query Engine for Big Data (by Facebook)

Apache Arrow logo Apache Arrow

Apache Arrow is a cross-language development platform for in-memory data.
  • Presto DB Landing page
    Landing page //
    2023-03-18
  • Apache Arrow Landing page
    Landing page //
    2021-10-03

Presto DB videos

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Apache Arrow videos

Wes McKinney - Apache Arrow: Leveling Up the Data Science Stack

More videos:

  • Review - "Apache Arrow and the Future of Data Frames" with Wes McKinney
  • Review - Apache Arrow Flight: Accelerating Columnar Dataset Transport (Wes McKinney, Ursa Labs)

Category Popularity

0-100% (relative to Presto DB and Apache Arrow)
Data Dashboard
100 100%
0% 0
Databases
39 39%
61% 61
Database Tools
100 100%
0% 0
NoSQL Databases
0 0%
100% 100

User comments

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Social recommendations and mentions

Based on our record, Apache Arrow should be more popular than Presto DB. It has been mentiond 33 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 Arrow mentions (33)

  • How moving from Pandas to Polars made me write better code without writing better code
    In comes Polars: a brand new dataframe library, or how the author Ritchie Vink describes it... a query engine with a dataframe frontend. Polars is built on top of the Arrow memory format and is written in Rust, which is a modern performant and memory-safe systems programming language similar to C/C++. - Source: dev.to / about 2 months ago
  • Time Series Analysis with Polars
    One is related to the heritage of being built around the NumPy library, which is great for processing numerical data, but becomes an issue as soon as the data is anything else. Pandas 2.0 has started to bring in Arrow, but it's not yet the standard (you have to opt-in and according to the developers it's going to stay that way for the foreseeable future). Also, pandas's Arrow-based features are not yet entirely on... - Source: dev.to / 5 months ago
  • TXR Lisp
    IMO a good first step would be to use the txr FFI to write a library for Apache arrow: https://arrow.apache.org/. - Source: Hacker News / 5 months ago
  • A Polars exploration into Kedro
    Polars is an open-source library for Python, Rust, and NodeJS that provides in-memory dataframes, out-of-core processing capabilities, and more. It is based on the Rust implementation of the Apache Arrow columnar data format (you can read more about Arrow on my earlier blog post “Demystifying Apache Arrow”), and it is optimised to be blazing fast. - Source: dev.to / 12 months ago
  • Demystifying Apache Arrow
    Apache Arrow (Arrow for short) is an open source project that defines itself as "a language-independent columnar memory format" (more on that later). It is part of the Apache Software Foundation, and as such is governed by a community of several stakeholders. It has implementations in several languages (C++ and also Rust, Julia, Go, and even JavaScript) and bindings for Python, R and others that wrap the C++... - Source: dev.to / 12 months ago
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What are some alternatives?

When comparing Presto DB and Apache Arrow, 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.

Delta Lake - Application and Data, Data Stores, and Big Data Tools

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

Redis - Redis is an open source in-memory data structure project implementing a distributed, in-memory key-value database with optional durability.

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 Parquet - Apache Parquet is a columnar storage format available to any project in the Hadoop ecosystem.