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Google BigQuery VS 30 seconds of code

Compare Google BigQuery VS 30 seconds of code and see what are their differences

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Google BigQuery logo Google BigQuery

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

30 seconds of code logo 30 seconds of code

JS snippets that you can understand in 30 seconds or less.
  • Google BigQuery Landing page
    Landing page //
    2023-10-03
  • 30 seconds of code Landing page
    Landing page //
    2023-09-23

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.

30 seconds of code features and specs

  • Concise Snippets
    30 seconds of code offers short, well-commented snippets that provide quick solutions to common programming challenges, making it easy for developers to implement without extensive modification.
  • Educational Resource
    The snippets serve as a great educational tool for learning new coding techniques and JavaScript features, helping developers enhance their skills incrementally.
  • Community-Driven
    The repository is maintained by a community of developers, ensuring that the code is peer-reviewed and can be continuously improved through collective contributions.
  • Broad Coverage
    The repository covers a wide range of categories including arrays, objects, functions, and more, providing snippets for various common use cases in JavaScript development.
  • Readily Accessible
    Because the code is available on GitHub, it is easily accessible to anyone with an internet connection, promoting widespread usage and collaboration.

Possible disadvantages of 30 seconds of code

  • Not Always Best Practice
    Some snippets prioritize brevity over best practice, which may lead to less efficient or less readable code in real-world applications.
  • Lack of Context
    The snippets are often given without extensive context or surrounding code, which can make it challenging for beginners to understand how to integrate them into larger projects.
  • Limited Explanation
    Brief descriptions and comments may not suffice for someone who needs a deeper understanding of why the code works the way it does.
  • Outdated Code
    As JavaScript continues to evolve, some snippets might become outdated or less optimal compared to modern alternatives.
  • Over-Simplification
    While aimed at being quick solutions, some snippets might oversimplify complex problems, potentially leading developers to underestimate the underlying complexity.

Analysis of Google BigQuery

Overall verdict

  • Google BigQuery is a powerful and flexible data warehouse solution that suits a wide range of data analytics needs. Its ability to handle large volumes of data quickly makes it a preferred choice for organizations looking to leverage their data effectively.

Why this product is good

  • Google BigQuery is a fully-managed data warehouse that simplifies the analysis of large datasets. It is known for its scalability, speed, and integration with other Google Cloud services. It supports standard SQL, has built-in machine learning capabilities, and allows for seamless data integration from various sources. The serverless architecture means that users don't need to worry about infrastructure management, and its pay-as-you-go model provides cost efficiency.

Recommended for

  • Businesses requiring fast processing of large datasets
  • Organizations that already utilize Google Cloud services
  • Companies looking for a cost-effective, scalable analytics solution
  • Teams interested in using SQL for data analysis
  • Data scientists integrating machine learning with their data workflows

Analysis of 30 seconds of code

Overall verdict

  • 30 seconds of code can be considered a good resource due to its concise and clear presentation of useful code snippets. It helps developers learn and apply new concepts efficiently, making it a solid tool for learning and quick reference.

Why this product is good

  • 30 seconds of code is a collection of JavaScript snippets that are designed to be easily digestible and practical. It serves as a valuable resource for both beginners and experienced developers, offering a quick way to understand and implement common coding patterns and solutions. The snippets are well-documented and typically focus on performance, best practices, and simplicity.

Recommended for

  • Beginner developers looking to learn JavaScript concepts through examples.
  • Experienced developers seeking quick reference material.
  • Developers who value performance-oriented and well-documented code snippets.
  • Anyone looking for inspiration or quick solutions to common JavaScript problems.

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

30 seconds of code videos

+ Add

30 Seconds Of Code - Check This Curated Collection Of Useful JavaScript Snippets

Category Popularity

0-100% (relative to Google BigQuery and 30 seconds of code)

Google BigQuery

30 seconds of code

Data Dashboard
100 100%
Data Dashboard
0% 0
Developer Tools
0 0%
Developer Tools
100% 100
Big Data
100 100%
Big Data
0% 0
Productivity
0 0%
Productivity
100% 100

User comments

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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 30 seconds of code

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

30 seconds of code Reviews

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Social recommendations and mentions

Based on our record, Google BigQuery should be more popular than 30 seconds of code. It has been mentiond 42 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 / about 2 months 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 / 2 months 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 / 2 months ago
  • Study Notes 2.2.7: Managing Schedules and Backfills with BigQuery in Kestra
    BigQuery Documentation: Google Cloud BigQuery. - Source: dev.to / 5 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 / 7 months ago
View more

30 seconds of code mentions (6)

  • What are the best open source repos in github that a beginner should READ?
    You could also check out: 1. 30 seconds of code 2. JavaScript30 3. JavaScript Algorithms. Source: about 2 years ago
  • Awesome Github Repos to Master JAVASCRIPT
    😎 a quick reference with short solutions for your development needs in javascript -> 30-seconds-of-code. - Source: dev.to / over 2 years ago
  • This is my first blog!
    Hello everyone, my name is Thanh Cong Van, my friends usually call me Steven as my Vietnamese name is hard to pronounce. I am living in Toronto, due to the pandemic, I believe that some of my peers are living in different place right now. I am currently taking Computer Programming and Analysis at Seneca, all I want from my program is to have good skills on front-end development. People tend to love full stack... - Source: dev.to / almost 4 years ago
  • Open Source Development -W1
    The GitHub repo, I have interest in is "30 seconds of code" [https://github.com/30-seconds/30-seconds-of-code]. It is a website which provides short JavaScript code snippets for users. I find it very helpful for me when I work on my project later on. - Source: dev.to / almost 4 years ago
  • Hello Word!
    For my forked repo, I picked the 30-seconds-of-code (https://github.com/30-seconds/30-seconds-of-code). It’s a repo with short snippets of JavaScript code to help people coding in JavaScript. Very useful for people like me that are always learning something and trying different things. - Source: dev.to / almost 4 years ago
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What are some alternatives?

When comparing Google BigQuery and 30 seconds of code, 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?

CodeMyUI - Handpicked code snippets you can use in your web projects

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.

Codespace - A beautiful cross-platform code snippet manager

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.

DhiWise - DhiWise is a ProCode platform that helps you build clean, scalable, and customizable native and cross-platform apps. Focus on what matters as a programmer and let DhiWise do the rest.

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