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Amplication VS Google BigQuery

Compare Amplication VS Google BigQuery and see what are their differences

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Create production-ready applications with zero code sponsored
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Amplication logo Amplication

Instantly generate Node.js apps with GraphQL and REST API

Google BigQuery logo Google BigQuery

A fully managed data warehouse for large-scale data analytics.
  • Amplication Landing page
    Landing page //
    2023-09-10
  • Google BigQuery Landing page
    Landing page //
    2023-10-03

Amplication features and specs

  • Rapid development
    Amplication allows developers to quickly generate and modify backend applications, reducing development time significantly.
  • Open-source
    Being open-source, Amplication provides transparency and allows developers to contribute to the project, ensuring continuous improvement and community support.
  • Scalability
    Amplication's architecture is designed to be scalable, making it suitable for both small projects and large, complex applications.
  • Customizability
    Developers can easily customize the generated code to fit specific business requirements, providing flexibility in application development.
  • Integration capabilities
    Amplication supports integration with various databases and third-party services, enhancing the functionality of the generated applications.
  • User-friendly interface
    The platform boasts an intuitive interface that simplifies the application creation process even for developers with minimal experience.

Possible disadvantages of Amplication

  • Early-stage product
    As a relatively new product, Amplication might not have all the features and refinements of more mature backend development tools.
  • Learning curve
    Despite its user-friendly interface, there may still be a learning curve for developers unfamiliar with the concepts of automated backend generation.
  • Limited ecosystem
    Compared to longstanding platforms, Amplication has a smaller ecosystem of plugins, templates, and community resources.
  • Dependency on specific technologies
    Amplication may limit developers to specific technologies and frameworks, which could be a downside for projects requiring unconventional tech stacks.
  • Potential for over-reliance on automation
    Heavy reliance on automated tools like Amplication may lead to less understanding of underlying backend processes among developers.
  • Performance optimization
    Automatically generated code may require additional performance tuning and optimization compared to hand-crafted solutions.

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 Amplication

Overall verdict

  • Amplication is generally considered a good choice for developers looking for an easy-to-use platform that speeds up the development process without sacrificing flexibility or customization.

Why this product is good

  • Amplication is a powerful open-source development tool that simplifies the process of building back-end applications. It provides a user-friendly interface, accelerates development with automated code generation, and integrates seamlessly with various tech stacks. Developers appreciate its customization options and robust documentation, which help reduce the complexity and time required for back-end development.

Recommended for

  • Developers who want to quickly prototype and build back-end applications
  • Teams looking for a collaborative and open-source development tool
  • Projects that need scalable and maintainable back-end solutions
  • Users who want a tool that integrates easily with existing technologies

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

Amplication videos

+ Add

Bullet AC -100 CR Acoustic Guitar Amplication review by www.Guitarthai.com

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

Category Popularity

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

Amplication

Google BigQuery

APIs
100 100%
APIs
0% 0
Data Dashboard
0 0%
Data Dashboard
100% 100
Developer Tools
100 100%
Developer Tools
0% 0
Big Data
0 0%
Big Data
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 Amplication and Google BigQuery

Amplication Reviews

We have no reviews of Amplication yet.
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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 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

Social recommendations and mentions

Based on our record, Amplication should be more popular than Google BigQuery. It has been mentiond 71 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.

Amplication mentions (71)

  • Top 15 Open-Source Low-Code Projects with the Most GitHub Stars
    GitHub Https://github.com/amplication/amplication GitHub Stars 14.8k Most Recent Update on GitHub Within one day Open Source License Apache 2.0 Number of Active Contributors This Year 15 Acceptance of External PRs Yes Official Website Https://amplication.com/ Documentation Https://docs.amplication.com/. - Source: dev.to / about 2 years ago
  • Extending GitOps: Effortless continuous integration and deployment on Kubernetes
    The application used in this demonstration was generated through Amplication, which allows you to generate production-ready backend services - reliably, securely, and consistently. - Source: dev.to / over 2 years ago
  • Auth0 and Amplication: Simplifying Authentication in Your Applications
    Setting up Auth0 authentication in your Amplication application is easy. You can use the Auth0 plugin to add the required dependencies and configuration files to your application. The steps are as follows:. - Source: dev.to / almost 3 years ago
  • Node.js Worker Threads Vs. Child Processes: Which one should you use?
    Additionally, you can use tools like Amplication to bootstrap your Node.js applications easily and focus on these parallel processing techniques instead of wasting time on (re)building all the boilerplate code for your Node.js services. - Source: dev.to / almost 3 years ago
  • Top 6 ORMs for Modern Node.js App Development
    In addition, Prisma is supported by microservice code generation tools like Amplication. Prisma plugs directly into the code generated by Amplication. By doing so, you can utilize Prisma as an ORM layer for your databases and generate microservice code with ease in just a few clicks. - Source: dev.to / almost 3 years ago
View more

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 — 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 / 6 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 transferability—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 / 10 months ago
View more

What are some alternatives?

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

KeystoneJS - Open source framework for developing database-driven websites, applications and APIs in Node.js.

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

Hasura - Hasura is an open platform to build scalable app backends, offering a built-in database, search, user-management and more.

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.

Sheet 2 Site - Generate a website from 📗 Google Sheets

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.

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