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Google BigQuery VS Org mode

Compare Google BigQuery VS Org mode and see what are their differences

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  3. » Reviews
  4. » Alternatives

Google BigQuery logo Google BigQuery

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

Org mode logo Org mode

Org: an Emacs Mode for Notes, Planning, and Authoring
  • Google BigQuery Landing page
    Landing page //
    2023-10-03
  • Org mode Landing page
    Landing page //
    2022-04-15

Google BigQuery features and specs

  • Scalability
    BigQuery can effortlessly scale to handle large volumes of data due to its serverless architecture, thereby reducing the operational overhead of managing infrastructure.
  • Speed
    It leverages Google's infrastructure to provide high-speed data processing, making it possible to run complex queries on massive datasets in a matter of seconds.
  • Integrations
    BigQuery easily integrates with various Google Cloud Platform services, as well as other popular data tools like Looker, Tableau, and Power BI.
  • Automatic Optimization
    Features like automatic data partitioning and clustering help to optimize query performance without requiring manual tuning.
  • Security
    BigQuery provides robust security features including IAM roles, customer-managed encryption keys, and detailed audit logging.
  • Cost Efficiency
    The pricing model is based on the amount of data processed, which can be cost-effective for many use cases when compared to traditional data warehouses.
  • Managed Service
    Being fully managed, BigQuery takes care of database administration tasks such as scaling, backups, and patch management, allowing users to focus on their data and queries.

Possible disadvantages of Google BigQuery

  • Cost Predictability
    While the pay-per-use model can be cost-efficient, it can also make cost forecasting difficult. Unexpected large queries could lead to higher-than-anticipated costs.
  • Complexity
    The learning curve can be steep for those who are not already familiar with SQL or Google Cloud Platform, potentially requiring training and education.
  • Limited Updates
    BigQuery is optimized for read-heavy operations, and it can be less efficient for scenarios that require frequent updates or deletions of data.
  • Query Pricing
    Costs are based on the amount of data processed by each query, which may not be suitable for use cases that require frequent analysis of large datasets.
  • Data Transfer Costs
    While internal data movement within Google Cloud can be cost-effective, transferring data to or from other services or on-premises systems can incur additional costs.
  • Dependency on Google Cloud
    Organizations heavily invested in multi-cloud or hybrid-cloud strategies may find the dependency on Google Cloud limiting.
  • Cold Data Performance
    Query performance might be slower for so-called 'cold data,' or data that has not been queried recently, affecting the responsiveness for some workloads.

Org mode features and specs

  • Seamless Integration with Emacs
    Org mode is tightly integrated with Emacs, allowing users to take full advantage of Emacs' powerful text-editing capabilities and extensive customization options.
  • Outline-Based Workflow
    Org mode supports hierarchical organization of information, which makes it easy to structure content in a clear, logical manner and manage complex documents or projects.
  • Task Management
    Built-in TODO lists, scheduling, and deadline management features make it a powerful tool for personal productivity and project management.
  • Export Capabilities
    Org mode can export documents to a variety of formats including HTML, LaTeX, PDF, and Markdown, making it versatile for different publishing needs.
  • Customizability
    Highly customizable through Emacs Lisp, allowing users to tailor Org mode to their specific workflow requirements.
  • Community and Extensions
    A robust community and numerous extensions are available, providing additional functionality and support.

Possible disadvantages of Org mode

  • Steep Learning Curve
    Requires significant time and effort to learn, especially for users who are not already familiar with Emacs.
  • Emacs Dependency
    Org mode is dependent on Emacs, which might not appeal to users who prefer different text editors or Integrated Development Environments (IDEs).
  • Complexity
    While it's powerful, the extensive features and customization options can become overwhelming and lead to a complex setup.
  • Lack of Standalone Version
    There is no standalone version of Org mode; it requires Emacs, which can be a barrier for those who do not want to use Emacs.
  • User Interface
    The text-based interface might not be as intuitive or visually appealing as modern, graphical task management or note-taking applications.

Google BigQuery videos

+ Add

Cloud Dataprep Tutorial - Getting Started 101

More videos:

  • Review - Advanced Data Cleanup Techniques using Cloud Dataprep (Cloud Next '19)
  • Demo - Google Cloud Dataprep Premium product demo

Org mode videos

+ Add

org mode is awesome

More videos:

  • Review - 2018-11-14: Building a Second Brain in Org Mode - Tasshin Michael Fogleman

Category Popularity

0-100% (relative to Google BigQuery and Org mode)

Google BigQuery

Org mode

Data Dashboard
100 100%
Data Dashboard
0% 0
Task Management
0 0%
Task Management
100% 100
Big Data
100 100%
Big Data
0% 0
Project Management
0 0%
Project Management
100% 100

User comments

Share your experience with using Google BigQuery and Org mode. For example, how are they different and which one is better?
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Reviews

These are some of the external sources and on-site user reviews we've used to compare Google BigQuery and Org mode

Google BigQuery Reviews

Data Warehouse Tools
Google BigQuery: Similar to Snowflake, BigQuery offers a pay-per-use model with separate charges for storage and queries. Storage costs start around $0.01 per GB per month, while on-demand queries are billed at $5 per TB processed.
Source: peliqan.io
Top 6 Cloud Data Warehouses in 2023
You can also use BigQuery’s columnar and ANSI SQL databases to analyze petabytes of data at a fast speed. Its capabilities extend enough to accommodate spatial analysis using SQL and BigQuery GIS. Also, you can quickly create and run machine learning (ML) models on semi or large-scale structured data using simple SQL and BigQuery ML. Also, enjoy a real-time interactive...
Source: geekflare.com
Top 5 Cloud Data Warehouses in 2023
Google BigQuery is an incredible platform for enterprises that want to run complex analytical queries or “heavy” queries that operate using a large set of data. This means it’s not ideal for running queries that are doing simple filtering or aggregation. So if your cloud data warehousing needs lightning-fast performance on a big set of data, Google BigQuery might be a great...
Source: www.shipyardapp.com
Top 5 BigQuery Alternatives: A Challenge of Complexity
BigQuery's emergence as an attractive analytics and data warehouse platform was a significant win, helping to drive a 45% increase in Google Cloud revenue in the last quarter. The company plans to maintain this momentum by focusing on a multi-cloud future where BigQuery advances the cause of democratized analytics.
Source: blog.panoply.io
16 Top Big Data Analytics Tools You Should Know About
Google BigQuery is a fully-managed, serverless data warehouse that enables scalable analysis over petabytes of data. It is a Platform as a Service that supports querying using ANSI SQL. It also has built-in machine learning capabilities.
Source: www.analytixlabs.co.in

Org mode Reviews

Ask HN: Favorite note-taking software?
Before going full Org Mode, I used MS OneNote, and liked it very much. My notes from that period has tons of images and annotated screenshots dumped into them. I miss that in my Emacs workflow nowadays. My dream software would be pieces of Org Mode on a OneNote-like canvas, with support for easily pasting images and drawing on them (especially using a graphics tablet, or at...
Source: news.ycombinator.com

Social recommendations and mentions

Based on our record, Org mode should be more popular than Google BigQuery. It has been mentiond 180 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.

Google BigQuery mentions (42)

  • Every Database Will Support Iceberg — Here's Why
    This isn’t hypothetical. It’s already happening. Snowflake supports reading and writing Iceberg. Databricks added Iceberg interoperability via Unity Catalog. Redshift and BigQuery are working toward it. - Source: dev.to / 20 days ago
  • RisingWave Turns Four: Our Journey Beyond Democratizing Stream Processing
    Many of these companies first tried achieving real-time results with batch systems like Snowflake or BigQuery. But they quickly found that even five-minute batch intervals weren't fast enough for today's event-driven needs. They turn to RisingWave for its simplicity, low operational burden, and easy integration with their existing PostgreSQL-based infrastructure. - Source: dev.to / 24 days ago
  • How to Pitch Your Boss to Adopt Apache Iceberg?
    If your team is managing large volumes of historical data using platforms like Snowflake, Amazon Redshift, or Google BigQuery, you’ve probably noticed a shift happening in the data engineering world. A new generation of data infrastructure is forming — one that prioritizes openness, interoperability, and cost-efficiency. At the center of that shift is Apache Iceberg. - Source: dev.to / about 1 month ago
  • Study Notes 2.2.7: Managing Schedules and Backfills with BigQuery in Kestra
    BigQuery Documentation: Google Cloud BigQuery. - Source: dev.to / 3 months ago
  • Docker vs. Kubernetes: Which Is Right for Your DevOps Pipeline?
    Pro Tip: Use Kubernetes operators to extend its functionality for specific cloud services like AWS RDS or GCP BigQuery. - Source: dev.to / 6 months ago
View more

Org mode mentions (180)

  • Ask HN: Static Site (not blog) Generator?
    My favorite static site generator is Org mode[1] for Emacs. Org files are written using a feature-rich lightweight markup language[2] that is much more powerful than Markdown (e.g., plain text spreadsheets). Org files can be exported to HTML[3]. The reason I prefer Org for static site generation is not because I already use Emacs. I actually started using Emacs about 20 years ago specifically to use Org mode. [1]... - Source: Hacker News / 6 days ago
  • Reinventing notebooks as reusable Python programs
    "until recently, Jupyter notebooks were the only programming environment that let you see your data while you worked on it." This is false. Org-mode has had this functionality for over two decades. https://orgmode.org/. - Source: Hacker News / about 2 months ago
  • Emacs 2024 Changes
    Work - I use org-mode heavily for my personal project management and note keeping. - Source: dev.to / 4 months ago
  • My 2024 review
    While embracing analog tools, I've also refined my digital organization using ORG mode in Emacs. The system has evolved to become more structured and efficient. - Source: dev.to / 5 months ago
  • (Game)Dev with Emacs - Because it's not Already Hard Enough Without it
    Org mode. Org mode is just great for taking notes and organizing tasks. I might write a post on it one day. If you're interested, check out Org Mode in the mean time. - Source: dev.to / 8 months ago
View more

What are some alternatives?

When comparing Google BigQuery and Org mode, you can also consider the following products

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

Todoist - Todoist is a to-do list that helps you get organized, at work and in life.

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.

Workflowy - A better way to organize your mind.

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.

Trello - Infinitely flexible. Incredibly easy to use. Great mobile apps. It's free. Trello keeps track of everything, from the big picture to the minute details.

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