Software Alternatives, Accelerators & Startups

Google BigQuery VS Kotlin

Compare Google BigQuery VS Kotlin and see what are their differences

Google BigQuery logo Google BigQuery

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

Kotlin logo Kotlin

Statically typed Programming Language targeting JVM and JavaScript
  • Google BigQuery Landing page
    Landing page //
    2023-10-03
  • Kotlin Landing page
    Landing page //
    2023-05-09

We recommend LibHunt Kotlin for discovery and comparisons of trending Kotlin projects.

Google BigQuery videos

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

Kotlin videos

10 reasons to try Kotlin for Android development

More videos:

  • Review - What can Kotlin do for me? (GDD Europe '17)
  • Review - Java or Kotlin for Android Development – Which One Is Better?

Category Popularity

0-100% (relative to Google BigQuery and Kotlin)
Data Dashboard
100 100%
0% 0
Programming Language
0 0%
100% 100
Big Data
100 100%
0% 0
OOP
0 0%
100% 100

User comments

Share your experience with using Google BigQuery and Kotlin. For example, how are they different and which one is better?
Log in or Post with

Reviews

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

Google BigQuery Reviews

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...
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.

Kotlin Reviews

Top 10 Rust Alternatives
The last computer programming language to stand out as an exceptional alternative to Rust is named Kotlin. It is typed statically and was manufactured for Java machines.

Social recommendations and mentions

Based on our record, Kotlin should be more popular than Google BigQuery. It has been mentiond 75 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 (35)

  • Swirl: An open-source search engine with LLMs and ChatGPT to provide all the answers you need 🌌
    Using the Galaxy UI, knowledge workers can systematically review the best results from all configured services including Apache Solr, ChatGPT, Elastic, OpenSearch, PostgreSQL, Google BigQuery, plus generic HTTP/GET/POST with configurations for premium services like Google's Programmable Search Engine, Miro and Northern Light Research. - Source: dev.to / 9 months ago
  • Modern data stack: scaling people and technology at FINN
    Data Transformations: This phase involves modifying and integrating tables to generate new tables optimized for analytical use. Consider this example: you want to understand the purchasing behavior of customers aged between 20-30 in your online shop. This means you'll need to join product, customer, and transaction data to create a unified table for analytics. These data preparation tasks (e.g., joining... - Source: dev.to / 9 months ago
  • Running Transformations on BigQuery using dbt Cloud: step by step
    Introduction In today's data-driven world, transforming raw data into valuable insights is crucial. This process, however, often involves complex tasks that demand efficiency, scalability, and reliability. Enter dbt Cloud—a powerful tool that simplifies data transformations on Google BigQuery. In this article, we'll take you through a step-by-step guide on how to run BigQuery transformations using dbt Cloud.... - Source: dev.to / 10 months ago
  • Do I need a cloud computing–based data cloud company
    You'll want to evaluate what BigQuery has to offer and see if it makes sense for you to move over. Source: 11 months ago
  • I used ChatGPT to get an Internship
    Watch the introductory videos on BigQuery on the Google Cloud Platform website (https://cloud.google.com/bigquery). Source: 11 months ago
View more

Kotlin mentions (75)

  • Moving your bugs forward in time
    ‍For the rest of this post I’ll list off some more tactical examples of things that you can do towards this goal. Savvy readers will note that these are not novel ideas of my own, and in fact a lot of the things on this list are popular core features in modern languages such as Kotlin, Rust, and Clojure. Kotlin, in particular, has done an amazing job of emphasizing these best practices while still being an... - Source: dev.to / 28 days ago
  • Implementing an Auto-logout Feature for Android in Kotlin
    A basic understanding of Kotlin and programming in general (OOP). - Source: dev.to / about 2 months ago
  • Kotlin and Azure Functions - Automating the deployment
    Being somewhat allergic to coding in Java (this is a personal thing, if you like Java then good for you) I decided to try out writing the code using Kotlin from JetBrains instead. I'm already using IntelliJ as I work with Apache Spark using Scala, so the tooling was already there and ready to go for this. - Source: dev.to / 3 months ago
  • 🎉 Kotlin Multiplatform is now STABLE!
    Congrats to our friends at Kotlin. 🚀 After years of growth and development, KMP reaches a pivotal milestone with 1.9.20. We’ve been on team Kotlin Multiplatform since day one, and the best is yet to come! Learn more 👉 https://touchlab.co/kotlin-multiplatform-is-stable. Source: 7 months ago
  • Regarding Lenses, Prisms and Optics
    Another option could be to check out Kotlin. It's a JVM language that while still object-oriented has may functional syntax features. Source: 8 months ago
View more

What are some alternatives?

When comparing Google BigQuery and Kotlin, 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?

Dart - A new web programming language with libraries, a virtual machine, and tools

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.

Python - Python is a clear and powerful object-oriented programming language, comparable to Perl, Ruby, Scheme, or Java.

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.

Elixir - Dynamic, functional language designed for building scalable and maintainable applications