Google BigQuery聽vs聽Google Cloud Storage

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Google BigQuery
Google BigQuery

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Google Cloud Storage
Google Cloud Storage

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Google BigQuery vs Google Cloud Storage: What are the differences?

Google BigQuery: Analyze terabytes of data in seconds. Run super-fast, SQL-like queries against terabytes of data in seconds, using the processing power of Google's infrastructure Load data with ease. Bulk load your data using Google Cloud Storage or stream it in. Easy access. Access BigQuery by using a browser tool, a command-line tool, or by making calls to the BigQuery REST API with client libraries such as Java, PHP or Python.; Google Cloud Storage: Durable and highly available object storage service. Google Cloud Storage allows world-wide storing and retrieval of any amount of data and at any time. It provides a simple programming interface which enables developers to take advantage of Google's own reliable and fast networking infrastructure to perform data operations in a secure and cost effective manner. If expansion needs arise, developers can benefit from the scalability provided by Google's infrastructure.

Google BigQuery belongs to "Big Data as a Service" category of the tech stack, while Google Cloud Storage can be primarily classified under "Cloud Storage".

Some of the features offered by Google BigQuery are:

  • All behind the scenes- Your queries can execute asynchronously in the background, and can be polled for status.
  • Import data with ease- Bulk load your data using Google Cloud Storage or stream it in bursts of up to 1,000 rows per second.
  • Affordable big data- The first Terabyte of data processed each month is free.

On the other hand, Google Cloud Storage provides the following key features:

  • High Capacity and Scalability
  • Strong Data Consistency
  • Google Developers Console Projects

"High Performance" is the primary reason why developers consider Google BigQuery over the competitors, whereas "Scalable" was stated as the key factor in picking Google Cloud Storage.

According to the StackShare community, Google Cloud Storage has a broader approval, being mentioned in 183 company stacks & 79 developers stacks; compared to Google BigQuery, which is listed in 160 company stacks and 41 developer stacks.

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What is Google BigQuery?

Run super-fast, SQL-like queries against terabytes of data in seconds, using the processing power of Google's infrastructure. Load data with ease. Bulk load your data using Google Cloud Storage or stream it in. Easy access. Access BigQuery by using a browser tool, a command-line tool, or by making calls to the BigQuery REST API with client libraries such as Java, PHP or Python.

What is Google Cloud Storage?

Google Cloud Storage allows world-wide storing and retrieval of any amount of data and at any time. It provides a simple programming interface which enables developers to take advantage of Google's own reliable and fast networking infrastructure to perform data operations in a secure and cost effective manner. If expansion needs arise, developers can benefit from the scalability provided by Google's infrastructure.
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    What are some alternatives to Google BigQuery and Google Cloud Storage?
    Google Cloud Bigtable
    Google Cloud Bigtable offers you a fast, fully managed, massively scalable NoSQL database service that's ideal for web, mobile, and Internet of Things applications requiring terabytes to petabytes of data. Unlike comparable market offerings, Cloud Bigtable doesn't require you to sacrifice speed, scale, or cost efficiency when your applications grow. Cloud Bigtable has been battle-tested at Google for more than 10 years鈥攊t's the database driving major applications such as Google Analytics and Gmail.
    Amazon Redshift
    It is optimized for data sets ranging from a few hundred gigabytes to a petabyte or more and costs less than $1,000 per terabyte per year, a tenth the cost of most traditional data warehousing solutions.
    Hadoop
    The Apache Hadoop software library is a framework that allows for the distributed processing of large data sets across clusters of computers using simple programming models. It is designed to scale up from single servers to thousands of machines, each offering local computation and storage.
    Snowflake
    Snowflake eliminates the administration and management demands of traditional data warehouses and big data platforms. Snowflake is a true data warehouse as a service running on Amazon Web Services (AWS)鈥攏o infrastructure to manage and no knobs to turn.
    Google Analytics
    Google Analytics lets you measure your advertising ROI as well as track your Flash, video, and social networking sites and applications.
    See all alternatives
    Decisions about Google BigQuery and Google Cloud Storage
    Snowflake
    Snowflake
    Google BigQuery
    Google BigQuery

    I use Google BigQuery because it makes is super easy to query and store data for analytics workloads. If you're using GCP, you're likely using BigQuery. However, running data viz tools directly connected to BigQuery will run pretty slow. They recently announced BI Engine which will hopefully compete well against big players like Snowflake when it comes to concurrency.

    What's nice too is that it has SQL-based ML tools, and it has great GIS support!

    See more
    GitHub
    GitHub
    Google Compute Engine
    Google Compute Engine
    Google Cloud Storage
    Google Cloud Storage
    Google BigQuery
    Google BigQuery
    Google Cloud Bigtable
    Google Cloud Bigtable
    Google Cloud Run
    Google Cloud Run
    Google Cloud Build
    Google Cloud Build
    Google Cloud Deployment Manager
    Google Cloud Deployment Manager
    Python
    Python
    Terraform
    Terraform
    Google Cloud IoT Core
    Google Cloud IoT Core

    Context: I wanted to create an end to end IoT data pipeline simulation in Google Cloud IoT Core and other GCP services. I never touched Terraform meaningfully until working on this project, and it's one of the best explorations in my development career. The documentation and syntax is incredibly human-readable and friendly. I'm used to building infrastructure through the google apis via Python , but I'm so glad past Sung did not make that decision. I was tempted to use Google Cloud Deployment Manager, but the templates were a bit convoluted by first impression. I'm glad past Sung did not make this decision either.

    Solution: Leveraging Google Cloud Build Google Cloud Run Google Cloud Bigtable Google BigQuery Google Cloud Storage Google Compute Engine along with some other fun tools, I can deploy over 40 GCP resources using Terraform!

    Check Out My Architecture: CLICK ME

    Check out the GitHub repo attached

    See more
    Interest over time
    Reviews of Google BigQuery and Google Cloud Storage
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    How developers use Google BigQuery and Google Cloud Storage
    Avatar of ShareThis
    ShareThis uses Google BigQueryGoogle BigQuery

    BigQuery allows our team to pull reports quickly using a SQL-like queries against our large store of data about social sharing. We use the information throughout the company, to do everything from making internal product decisions based on usage patterns to sharing certain kinds of custom reports with our publishers.

    Avatar of Lyndon Wong
    Lyndon Wong uses Google BigQueryGoogle BigQuery

    Aggregation of user events and traits across a marketing website, SaaS web application, user account provisioning backend and Salesforce CRM. Enables full-funnel analysis of campaign ROI, customer acquisition, engagement and retention at both the user and target account level.

    Avatar of itzMe
    itzMe uses Google Cloud StorageGoogle Cloud Storage

    Amazon / Google... Google / Amazon ... we decided to take the plunge and go for Google Cloud services as their services seem to be a bit more thought through and structured as they have not developed so organically.

    Avatar of Matt Welke
    Matt Welke uses Google Cloud StorageGoogle Cloud Storage

    When creating proofs of concept or small personal projects that are hosted primarily in GCP, this is the object storage service I usually pair them with.

    Avatar of Flutter Health Inc.
    Flutter Health Inc. uses Google Cloud StorageGoogle Cloud Storage

    We use Google Cloud Storage to store the images and other files that are added (uploaded) or generated in the Flutter application.

    Avatar of CommentBox.io
    CommentBox.io uses Google Cloud StorageGoogle Cloud Storage

    All comments, votes, and other actions live here as a highly-scalable, reliable, multi-region storage solution.

    Avatar of Blue Shell Games
    Blue Shell Games uses Google BigQueryGoogle BigQuery

    Google's insanely fast, feature-rich, zero-maintenance column store. Used for real-time customer data queries.

    Avatar of Cirrus Labs
    Cirrus Labs uses Google Cloud StorageGoogle Cloud Storage

    Cirrus CI can store build artifacts in Google Cloud Storage

    How much does Google BigQuery cost?
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