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Platfora VS Presto DB

Compare Platfora VS Presto DB and see what are their differences

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Platfora logo Platfora

BI and Analytics Platform

Presto DB logo Presto DB

Distributed SQL Query Engine for Big Data (by Facebook)
  • Platfora Landing page
    Landing page //
    2018-10-16
  • Presto DB Landing page
    Landing page //
    2023-03-18

Platfora features and specs

  • User-Friendly Interface
    Platfora offers an intuitive and user-friendly interface that allows users to create and analyze big data visualizations with minimal training.
  • Unified Data Platform
    The platform integrates data preparation, data analysis, and data visualization capabilities into one cohesive solution, reducing the need for multiple tools.
  • Real-Time Analytics
    Platfora provides real-time data processing and analytics, enabling users to make timely and informed decisions based on up-to-date information.
  • Scalability
    Designed to handle large volumes of data, Platfora can scale to meet the needs of growing organizations and extensive data sets.
  • Big Data Compatibility
    Platfora is compatible with major big data platforms like Hadoop, allowing for seamless integration into existing data ecosystems.
  • Customizable Dashboards
    Users can create customized dashboards to monitor key performance indicators and other critical metrics specific to their business needs.

Possible disadvantages of Platfora

  • Cost
    Platfora can be expensive, particularly for small and medium-sized businesses, due to its enterprise-level capabilities and features.
  • Complex Implementation
    Setting up Platfora can be complex and may require IT support and significant initial configuration, which could be a barrier for less technically skilled teams.
  • Learning Curve
    Despite its user-friendly interface, there can still be a learning curve associated with fully utilizing all the advanced features and functionalities.
  • Limited Third-Party Integrations
    Although Platfora integrates well with big data platforms, it may have limited compatibility with other third-party tools and software, potentially requiring additional custom integrations.
  • Resource Intensive
    Operating Platfora can demand significant computational resources, potentially requiring investments in hardware or cloud infrastructure.

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.

Analysis of Platfora

Overall verdict

  • Platfora is generally regarded as a good solution for businesses aiming to capitalize on big data analytics, particularly those that use Hadoop environments. Its user-friendly interface and powerful analytics capabilities help it stand out as a viable platform for data exploration and visualization.

Why this product is good

  • Platfora is a data discovery tool designed to help users analyze big data and transform it into actionable insights. It is particularly known for its ability to work directly with Hadoop data, providing an interactive and intuitive interface for users to explore data without the need for complex programming skills. This makes it a strong choice for organizations looking to leverage big data analytics with relative ease. Its interactive visualizations and ability to process large datasets efficiently make it a powerful tool for data-driven decision-making.

Recommended for

    Platfora is recommended for data analysts, business intelligence professionals, and organizations that utilize Hadoop and need a scalable, intuitive solution for big data analytics. It is suitable for medium to large enterprises that require deep analytics and insights drawn from complex datasets.

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.

Platfora videos

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Pete Schlampp, Platfora - #BigDataSV 2016 - #theCUBE

Presto DB videos

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Category Popularity

0-100% (relative to Platfora and Presto DB)

Platfora

Presto DB

Data Dashboard
20 20%
Data Dashboard
80% 80
Development
100 100%
Development
0% 0
Database Tools
10 10%
Database Tools
90% 90
Big Data Analytics
0 0%
Big Data Analytics
100% 100

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.

Platfora mentions (0)

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

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 / about 1 month 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 / about 1 month 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 / about 2 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 / 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
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What are some alternatives?

When comparing Platfora and Presto DB, 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.

Rakam - Custom analytics platform

Databricks - Databricks provides a Unified Analytics Platform that accelerates innovation by unifying data science, engineering and business.‎What is Apache Spark?

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.

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