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Google BigQuery VS Stackshare

Compare Google BigQuery VS Stackshare and see what are their differences

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Contents:
  1. ยป Base Details
  2. ยป Videos
  3. ยป Reviews
  4. ยป Alternatives

Google BigQuery logo Google BigQuery

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

Stackshare logo Stackshare

StackShare is a comprehensive website that gives its users the chance to organize and share their technology stack with the rest of the community.
  • Google BigQuery Landing page
    Landing page //
    2023-10-03
  • Stackshare Landing page
    Landing page //
    2022-12-20

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.

Stackshare features and specs

  • Comprehensive Technology Stack Information
    Stackshare provides detailed information about various technologies, including programming languages, frameworks, libraries, and tools. This helps users to make informed decisions about the technology stacks they should use for their projects.
  • User-Generated Reviews
    The platform allows users to share their experiences and reviews about the tools and technologies they use. This social proof can be valuable for others considering similar technologies.
  • Comparisons and Alternatives
    Stackshare allows users to compare different technologies side-by-side and explore alternatives, which can be useful for evaluating the pros and cons of various options.
  • Community and Networking
    Users can follow companies and their tech stacks, engage in discussions, and connect with other professionals, fostering a sense of community and networking opportunities.
  • Technology Trends
    The platform provides insights into current technology trends and popular tools, helping users stay updated with the latest advancements in the tech industry.

Possible disadvantages of Stackshare

  • Limited Depth in Some Areas
    While Stackshare offers a broad overview of many technologies, it might lack in-depth information or expert analysis on some specific tools or less popular technologies.
  • Reliance on User-Generated Content
    The quality and accuracy of the information can vary since a significant portion of the content comes from user contributions. This can be both a strength and a weakness.
  • Potential for Bias
    User reviews and recommendations can be subjective and may reflect personal biases or isolated experiences, which might not always be representative of the general consensus.
  • Login Requirement
    To access full features and contribute to the platform, users need to create an account and log in, which might be a barrier for those looking for quick information.
  • Not Always Up-to-Date
    Some information on the site can become outdated as technology rapidly evolves. Users need to verify that the data they are relying on is current.

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 Stackshare

Overall verdict

  • Stackshare.io is a beneficial resource for those looking to understand and decide on the technology stacks used in software development. Its comprehensive database and user-friendly interface make it a good platform for tech stack comparison and discovery.

Why this product is good

  • Stackshare.io is a valuable platform for developers, product managers, and tech enthusiasts who want to choose the best software stack for their projects. It offers insights into the tools and technologies used by various companies and the ability to compare tools based on features, popularity, and user reviews. The community-driven content allows users to learn from real-world use cases and experiences shared by peers.

Recommended for

  • Software developers looking to explore and compare technology stacks.
  • Product managers needing insights into popular technology choices.
  • Tech startups aiming to build their initial technology stack.
  • Enterprises seeking to update or refine their existing technology setup based on industry trends.

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

Stackshare videos

+ Add

[500 STARTUPS DEMO DAY 2015] BATCH 14, StackShare

More videos:

  • Review - StackShare- Kelli Lampkin

Category Popularity

0-100% (relative to Google BigQuery and Stackshare)

Google BigQuery

Stackshare

Data Dashboard
100 100%
Data Dashboard
0% 0
Software Marketplace
0 0%
Software Marketplace
100% 100
Big Data
100 100%
Big Data
0% 0
Software Recommendations
0 0%
Software Recommendations
100% 100

User comments

Share your experience with using Google BigQuery and Stackshare. 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 Stackshare

Google BigQuery Reviews

Database for Data Analytics
Processing typeDescriptionUse casesCommon databasesProcessing typesProcesses data in scheduled intervals (hours, days). High-latency but cost-efficient for large datasets.Financial reporting, trend analysis, historical analyticsSnowflake, Amazon Redshift, Google BigQueryContinuously ingests and processes data with minimal latency for real-time decision-making.Fraud...
Source: blog.devart.com
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 BigQueryโ€™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 โ€œheavyโ€ queries that operate using a large set of data. This means itโ€™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

Stackshare Reviews

Software Launch Platforms: Leading Product Hunt Alternatives
Stackshare is a developer-centric platform that allows users to explore, compare, and build stacks using popular software tools. With a strong focus on developers, Stackshare offers an excellent opportunity to showcase software products and gain traction with a technical audience.
Source: www.cccreative.design
Exploring SaaS Directories: The Path to Optimal Software Selection
StackShare offers insights into the technology stacks of various companies, including SaaS products, tools, and services used, aiding businesses in technology decision-making, providing valuable insights for software architecture planning. stackshare.io
Source: cloudtweaks.com

Social recommendations and mentions

Based on our record, Google BigQuery should be more popular than Stackshare. It has been mentiond 47 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 (47)

  • Ruby on Rails Performance: 7 Lessons from Scaling FirstPromoter
    We migrated the analytics layer to Google BigQuery. Same queries that timed out in PostgreSQL now run in under 2 seconds. But not everything belongs in BigQuery โ€” we initially moved too aggressively and actually reverted some queries back when the added complexity wasn't justified. Our rule of thumb: if a query scans hundreds of thousands of rows or involves complex time-series aggregations, BigQuery. Everything... - Source: dev.to / 5 months ago
  • How to Analyze 47 Million Hacker News Posts: A Data Scientist's Dream Dataset Just Got Better
    Google BigQuery - For large-scale data processing and SQL-based analysis. - Source: dev.to / 5 months ago
  • What if ML pipelines had a lock file?
    Data Pipelines usually read from tables that change over time. Most of these tables are stored in a data warehouse like Amazon Redshift or Google BigQuery. Rows are added or removed. Backfills happen. A column gets renamed or its meaning changes. Even when teams snapshot data, those snapshots are often implicit, not recorded as part of the pipeline run itself. - Source: dev.to / 7 months ago
  • Best SQL Courses with Certificates for 2026
    SQL endures because it's the non-negotiable interface for relational data. Enterprise data storage still relies heavily on relational databases despite new alternatives. What makes SQL valuable for learners is transferabilityโ€”while dialects differ across PostgreSQL, SQL Server, and BigQuery, the fundamentals stay consistent. - Source: dev.to / 9 months ago
  • Why Your Snowflake Bill is High and How to Fix It with a Hybrid Approach
    Within classic cloud data warehouses, Google BigQuery presents a different pricing model. Its on-demand, per-terabyte-scanned pricing can be cost-effective for sporadic forensic queries. But it carries the risk of a runaway query where a single mistake leads to a massive bill. - Source: dev.to / 9 months ago
View more

Stackshare mentions (26)

  • Ask HN: Which apps tell you about which shoulders of giants they stand on
    For web apps, see https://stackshare.io/ For many desktop apps, if you go into Help > About, you'll see a list of all the open source libraries used, and their associated licenses (as required by the license). In Chrome, go to chrome://credits/. - Source: Hacker News / about 2 years ago
  • Tech radar: Keep an eye on the technology landscape
    Stackshare - Aimed for companies building their technical stack. - Source: dev.to / about 2 years ago
  • "What tech stack does this person use" - Are there any articles/wikis that lists of solution tech stacks of famous engineers or STEM "influencers" / content creators?
    I don't know much about 'influencers' but https://builtwith.com/ is good for seeing what some public facing website is built with, https://stackshare.io/ tends to have a little more information about backends of sites and https://usesthis.com/ has a lot of interviews with various people about what they use. Source: over 3 years ago
  • A question on tech stack for experienced technical-founders
    You could look at https://stackshare.io/ for some inspiration or validation. Source: over 3 years ago
  • Ask HN: How do you get companies to talk to you about their problems?
    - look at databases of tech stacks (https://stackshare.io/ is one), the company websites where any logos were mentioned, anywhere we could get an info that this company was using one of the alternative tools. - Source: Hacker News / over 3 years ago
View more

What are some alternatives?

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

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

AlternativeTo - AlternativeTo lets you find apps and software for Windows, Mac, Linux, iPhone, iPad, Android, Android Tablets, Web Apps, Online, Windows Tablets and more by recommending alternatives to apps you already know.

Looker - Looker makes it easy for analysts to create and curate custom data experiencesโ€”so everyone in the business can explore the data that matters to them, in the context that makes it truly meaningful.

Product Hunt - A website that lets users share and discover new products

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.

Slant.co - Slant is a collaboratively edited resource that helps you quickly make decisions.

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