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Google Cloud Bigtable

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270
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21
Serverless

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965
+ 1
23
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Google Cloud Bigtable vs Serverless: What are the differences?

Google Cloud Bigtable: The same database that powers Google Search, Gmail and Analytics. 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—it's the database driving major applications such as Google Analytics and Gmail; Serverless: The most widely-adopted toolkit for building serverless applications. Build applications comprised of microservices that run in response to events, auto-scale for you, and only charge you when they run. This lowers the total cost of maintaining your apps, enabling you to build more logic, faster. The Framework uses new event-driven compute services, like AWS Lambda, Google CloudFunctions, and more.

Google Cloud Bigtable and Serverless are primarily classified as "NoSQL Database as a Service" and "Serverless / Task Processing" tools respectively.

"High performance" is the primary reason why developers consider Google Cloud Bigtable over the competitors, whereas "API integration " was stated as the key factor in picking Serverless.

Serverless is an open source tool with 30.5K GitHub stars and 3.38K GitHub forks. Here's a link to Serverless's open source repository on GitHub.

According to the StackShare community, Serverless has a broader approval, being mentioned in 112 company stacks & 43 developers stacks; compared to Google Cloud Bigtable, which is listed in 17 company stacks and 3 developer stacks.

Decisions about Google Cloud Bigtable and Serverless

When adding a new feature to Checkly rearchitecting some older piece, I tend to pick Heroku for rolling it out. But not always, because sometimes I pick AWS Lambda . The short story:

  • Developer Experience trumps everything.
  • AWS Lambda is cheap. Up to a limit though. This impact not only your wallet.
  • If you need geographic spread, AWS is lonely at the top.
The setup

Recently, I was doing a brainstorm at a startup here in Berlin on the future of their infrastructure. They were ready to move on from their initial, almost 100% Ec2 + Chef based setup. Everything was on the table. But we crossed out a lot quite quickly:

  • Pure, uncut, self hosted Kubernetes — way too much complexity
  • Managed Kubernetes in various flavors — still too much complexity
  • Zeit — Maybe, but no Docker support
  • Elastic Beanstalk — Maybe, bit old but does the job
  • Heroku
  • Lambda

It became clear a mix of PaaS and FaaS was the way to go. What a surprise! That is exactly what I use for Checkly! But when do you pick which model?

I chopped that question up into the following categories:

  • Developer Experience / DX 🤓
  • Ops Experience / OX 🐂 (?)
  • Cost 💵
  • Lock in 🔐

Read the full post linked below for all details

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Pros of Google Cloud Bigtable
Pros of Serverless
  • 8
    Fully managed
  • 8
    High performance
  • 5
    High scalability
  • 12
    API integration
  • 7
    Supports cloud functions for Google, Azure, and IBM
  • 2
    Lower cost
  • 1
    Openwhisk
  • 1
    Auto scale

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- No public GitHub repository available -

What is 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—it's the database driving major applications such as Google Analytics and Gmail.

What is Serverless?

Build applications comprised of microservices that run in response to events, auto-scale for you, and only charge you when they run. This lowers the total cost of maintaining your apps, enabling you to build more logic, faster. The Framework uses new event-driven compute services, like AWS Lambda, Google CloudFunctions, and more.

Need advice about which tool to choose?Ask the StackShare community!

What companies use Google Cloud Bigtable?
What companies use Serverless?
See which teams inside your own company are using Google Cloud Bigtable or Serverless.
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What tools integrate with Google Cloud Bigtable?
What tools integrate with Serverless?

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What are some alternatives to Google Cloud Bigtable and Serverless?
Google Cloud Datastore
Use a managed, NoSQL, schemaless database for storing non-relational data. Cloud Datastore automatically scales as you need it and supports transactions as well as robust, SQL-like queries.
Microsoft Access
It is an easy-to-use tool for creating business applications, from templates or from scratch. With its rich and intuitive design tools, it can help you create appealing and highly functional applications in a minimal amount of time.
Google Cloud Spanner
It is a globally distributed database service that gives developers a production-ready storage solution. It provides key features such as global transactions, strongly consistent reads, and automatic multi-site replication and failover.
MongoDB
MongoDB stores data in JSON-like documents that can vary in structure, offering a dynamic, flexible schema. MongoDB was also designed for high availability and scalability, with built-in replication and auto-sharding.
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.
See all alternatives