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Presto DB VS Concurrent

Compare Presto DB VS Concurrent and see what are their differences

Presto DB logo Presto DB

Distributed SQL Query Engine for Big Data (by Facebook)

Concurrent logo Concurrent

Concurrent is a technology solution providing real-time computing solutions for businesses and individuals.
  • Presto DB Landing page
    Landing page //
    2023-03-18
  • Concurrent Landing page
    Landing page //
    2023-07-13

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.

Concurrent features and specs

  • Scalable Data Processing
    Concurrent provides tools that enable scalable data processing on distributed systems, which can handle large datasets and complex pipelines efficiently.
  • Open Source Tools
    The company offers open-source tools, such as Cascading, which allows developers to build powerful data applications and workflows without being tied to proprietary solutions.
  • Integration with Hadoop
    Concurrent provides strong integration with Hadoop, allowing users to leverage the vast Hadoop ecosystem for advanced data processing capabilities.
  • Developer Productivity
    By using tools like Cascading, developers can focus more on business logic rather than the intricacies of distributed computing and low-level detail plumbing.
  • Community Support
    Being based on open-source projects, Concurrent benefits from a large community of users and contributors, providing robust support and continuous improvements.

Possible disadvantages of Concurrent

  • Steep Learning Curve
    Tools like Cascading can have a steep learning curve for developers who are not already familiar with Hadoop and the MapReduce paradigm.
  • Dependency on Hadoop
    Strong integration with Hadoop can be a downside for organizations looking to migrate away from Hadoop or use different big data processing frameworks.
  • Performance Overhead
    Abstracting away lower-level details and focusing on developer productivity can sometimes introduce performance overhead compared to writing optimized, low-level code.
  • Complex Setups
    Setting up Cascading and related tooling within an organization's infrastructure might require significant time and effort, especially for teams with less experience in the big data domain.
  • Limited Vendor-Specific Features
    As open-source tools need to remain general and widely applicable, they may lack some of the specific features and optimizations provided by proprietary, vendor-specific solutions suited for particular use cases.

Presto DB videos

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Concurrent videos

LOCADTR Concurrent Review Module Walk Through

More videos:

  • Review - Concurrent Review Instructions
  • Review - Documentation Requirements for Claim Submission and Concurrent Review

Category Popularity

0-100% (relative to Presto DB and Concurrent)
Data Dashboard
65 65%
35% 35
Database Tools
64 64%
36% 36
Big Data Analytics
60 60%
40% 40
Databases
100 100%
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 / 8 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 / 8 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 / 23 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 / 3 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
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Concurrent mentions (0)

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

What are some alternatives?

When comparing Presto DB and Concurrent, 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.