Software Alternatives, Accelerators & Startups

Archbee.io VS Google BigQuery

Compare Archbee.io VS Google BigQuery 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.

Archbee.io logo Archbee.io

Archbee is a developer-focused product docs tool for your team. Build beautiful product documentation sites or internal wikis/knowledge bases to get your team and product knowledge in one place.

Google BigQuery logo Google BigQuery

A fully managed data warehouse for large-scale data analytics.
  • Archbee.io Landing page
    Landing page //
    2021-08-30

Write in a blazingly fast WYSIWYG editor with 30+ custom blocks and native markdown to create built-in diagrams, API docs, Swagger, GraphQL. Check the out of the box integrations with Github, Slack, Lucidchart, Airtable, Google Sheets, Typeform, Jira, or Figma. Inline comments for async collaboration and to enhance team performance or minimize knowledge churn are supported by Archbee's collaborative features.

Why Archbee?

  • Focused on engineering people’s needs.
  • Integrated CMS & hosting platform for docs to allow easy internal and external access.
  • One-click hosting with SEO support and layout templates.
  • Reduce knowledge churn and become remote-friendly.
  • Improve onboarding time and increase developer efficiency.

Effortless content editing and collaboration

  • 20+ Custom Blocks
  • Inline Comments
  • Links & Mentions
  • Markdown editing

Say goodbye to the slow and clunky

  • Drag & Drop to Organize
  • Flexible & Powerful Search
  • Infinite History
  • Access Control
  • Knowledge Graph
  • Google BigQuery Landing page
    Landing page //
    2023-10-03

Archbee.io

$ Details
freemium $30.0 / Monthly (5 users)
Platforms
Browser Windows Mac OSX Linux
Release Date
2019 May

Archbee.io features and specs

  • CDN & Image Optimization on your custom domains
  • Custom JavaScript
  • Custom CSS
  • Search Analytics for team and customer queries
  • JWT authentication for shared collections

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.

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

Archbee.io videos

Archbee.io Review- My Honest Opinion

More videos:

  • Demo - Archbee walkthrough

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

Category Popularity

0-100% (relative to Archbee.io and Google BigQuery)
Documentation
100 100%
0% 0
Data Dashboard
0 0%
100% 100
Developer Tools
100 100%
0% 0
Big Data
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 Archbee.io and Google BigQuery

Archbee.io Reviews

Best Gitbook Alternatives You Need to Try in 2023
One alternative to Gitbook is Archbee. A powerful platform that allows users to write, collaborate and publish self-service knowledge portals quickly. One of the main advantages of using Archbee is its simplicity combined with advanced documentation capabilities.
Source: www.archbee.com
12 Most Useful Knowledge Management Tools for Your Business
Archbee offers Mermaid, as well as Markdown through GitHub, and API capabilities, meaning it’s perfect for code documentation. In addition, 30+ custom blocks, as well as 25 embeds and integrations available, make this tool extremely versatile, covering most documentation needs.
Source: www.archbee.com

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.

Social recommendations and mentions

Based on our record, Google BigQuery should be more popular than Archbee.io. 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.

Archbee.io mentions (21)

  • How to simplify, self-contain and delegate work?
    If you have a tech business, you should look into an internal knowledge base that is aligned with developers. archbee.com is similar to document360, but with features that are relevant to write developer documentation, APIs etc. Source: almost 3 years ago
  • Best tool for creating GraphQL API documentation?
    But if you want something similar with your example, check archbee.com, it has integration with GraphiQL. Source: almost 3 years ago
  • How can I make API docs?
    If you want to get a tool and don't need to start building your own setup I would recommend looking into some documentation platforms like archbee.io. Source: almost 3 years ago
  • End user documentation tools - knowledge base / manual
    If you want to go with a SaaS, I'd say to check archbee.io - because you can do end user guides and developer documentation... Source: almost 3 years ago
  • What's your documentation stack?
    It's hard to enforce developers to update documentation. Ideally, you should have somebody responsible to do it. As for the documentation stack, archbee.io for both internal and external. A good alternative to Notion since it supports markdown, code blocks with more options and API references. Source: almost 3 years ago
View more

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 1 month 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 / about 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 / about 2 months ago
  • Study Notes 2.2.7: Managing Schedules and Backfills with BigQuery in Kestra
    BigQuery Documentation: Google Cloud BigQuery. - Source: dev.to / 4 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

What are some alternatives?

When comparing Archbee.io and Google BigQuery, you can also consider the following products

ReadMe - A collaborative developer hub for your API or code.

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

Slite - Your company knowledge

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.

Docusaurus - Easy to maintain open source documentation websites

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.