Software Alternatives, Accelerators & Startups

Google BigQuery VS Pythonista

Compare Google BigQuery VS Pythonista and see what are their differences

Note: These products don't have any matching categories. If you think this is a mistake, please edit the details of one of the products and suggest appropriate categories.

Google BigQuery logo Google BigQuery

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

Pythonista logo Pythonista

Bring the Zen of Python to iOS.
  • Google BigQuery Landing page
    Landing page //
    2023-10-03
  • Pythonista Landing page
    Landing page //
    2019-07-29

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.

Pythonista features and specs

  • User-Friendly Interface
    Pythonista offers a clean and intuitive interface that is easy to navigate, making it accessible for both beginners and experienced Python developers.
  • Extensive Built-in Libraries
    The app includes many useful libraries such as NumPy and Matplotlib, allowing for complex computations and data visualization directly on iOS devices.
  • iOS Integration
    Pythonista provides excellent integration with iOS features and functionalities, such as access to the clipboard, photos, and location data, enhancing app development possibilities.
  • Script Sharing
    Users can easily share their scripts via email or other apps, facilitating collaboration and sharing of Python code among peers.
  • Regular Updates
    Pythonista receives regular updates that introduce new features, library support, and improvements ensuring a robust and up-to-date development environment.

Possible disadvantages of Pythonista

  • Platform Limitation
    Pythonista is available exclusively for iOS, restricting its use to users who own Apple devices.
  • Limited to Python
    The app only supports the Python language, which can be a limitation for users who need a multi-language development environment.
  • No Native File System Access
    Due to iOS security restrictions, Pythonista does not provide native access to the file system, which might be a hurdle for some file manipulation tasks.
  • Paid Application
    Pythonista is not free, requiring an initial purchase, which might deter individuals who are looking for a free development environment.
  • Resource Intensive
    Running complex scripts or computations might be resource-intensive on older iOS devices, leading to slower performance or battery drainage.

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

Pythonista videos

Writing Python on iPad using Pythonista! In-Depth Review + Is it Worth it?

More videos:

  • Review - Coding On The iPad - Pythonista Modules - Create iOS Apps on iPad With Python!

Category Popularity

0-100% (relative to Google BigQuery and Pythonista)
Data Dashboard
100 100%
0% 0
Education
0 0%
100% 100
Big Data
100 100%
0% 0
Text Editors
0 0%
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 Pythonista

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...
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.

Pythonista Reviews

We have no reviews of Pythonista yet.
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Social recommendations and mentions

Based on our record, Google BigQuery should be more popular than Pythonista. 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 / 24 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 / 29 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

Pythonista mentions (11)

  • Maker of RStudio launches new R and Python IDE
    Pythonista is nicer but ships older Python: https://omz-software.com/pythonista/ Pyto is maybe less approachable but more up to date, with clang compiler and LLVM bitcode interpreter: https://pyto.app/ Juno is Python notebooks: https://juno.sh/https://juno.sh/ In general I prefer Blink Code: https://docs.blink.sh/advanced/code. - Source: Hacker News / 11 months ago
  • Ask HN: Why don't smartphones encourage programming like early 80s computers?
    There are a few Python environments for iOS, and I'm sure Android also has some. Pythonista is probably one of the better ones. http://omz-software.com/pythonista/. - Source: Hacker News / about 2 years ago
  • Remote development on a mobile device
    Haven't tried it, but there's Pythonista. You can also use a remote terminal like blink shell and ssh into a tmux session. I also haven't tried this, either. Source: almost 3 years ago
  • How to code, build, and deploy from an iPad using Gitlab and Gitpod
    There's Pythonista - works pretty well, and you can import modules. I use it for messing around with MQTT. http://omz-software.com/pythonista/. - Source: Hacker News / about 3 years ago
  • Does anybody have a way to trigger an automation after using Apple Pay?
    You can write and execute a script with Pythonista. Source: over 3 years ago
View more

What are some alternatives?

When comparing Google BigQuery and Pythonista, 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?

NOMone Desktop - Linux and VR - Try our desktop experience running entirely on your smartphone/tablet/smart TV. Phone screen is too small, or just want to work from bed? Try our VR mode!

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.

Py - Learn to code on the go 📱

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.

QPython 3L - QPython is the Python engine for android. It contains some amazing features such as Python interpreter, runtime environment, editor, QPYI and SL4A library. It makes it easy for you to use Python on Android. QPython 3L is also an open source app.