Software Alternatives, Accelerators & Startups

AWS Lambda VS Google Cloud Bigtable

Compare AWS Lambda VS Google Cloud Bigtable 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.

AWS Lambda logo AWS Lambda

Automatic, event-driven compute service

Google Cloud Bigtable logo Google Cloud Bigtable

A high performance NoSQL database service for large analytical and operational workloads.
  • AWS Lambda Landing page
    Landing page //
    2023-04-29
  • Google Cloud Bigtable Landing page
    Landing page //
    2023-09-12

AWS Lambda features and specs

  • Scalability
    AWS Lambda automatically scales your application by running your code in response to each trigger. This means no manual intervention is required to handle varying levels of traffic.
  • Cost-effectiveness
    You only pay for the compute time you consume. Billing is metered in increments of 100 milliseconds and you are not charged when your code is not running.
  • Reduced Operations Overhead
    AWS Lambda abstracts the infrastructure management layer, so there is no need to manage or provision servers. This allows you to focus more on writing code for your applications.
  • Flexibility
    Supports multiple programming languages such as Python, Node.js, Ruby, Java, Go, and .NET, which allows you to use the language you are most comfortable with.
  • Integration with Other AWS Services
    Seamlessly integrates with many other AWS services such as S3, DynamoDB, RDS, SNS, and more, making it versatile and highly functional.
  • Automatic Scaling and Load Balancing
    Handles thousands of concurrent requests without managing the scaling yourself, making it suitable for applications requiring high availability and reliability.

Possible disadvantages of AWS Lambda

  • Cold Start Latency
    The first request to a Lambda function after it has been idle for a certain period can take longer to execute. This is referred to as a 'cold start' and can impact performance.
  • Resource Limits
    Lambda has defined limits, such as a maximum execution timeout of 15 minutes, memory allocation ranging from 128 MB to 10,240 MB, and temporary storage up to 512 MB.
  • Vendor Lock-in
    Using AWS Lambda ties you into the AWS ecosystem, making it difficult to migrate to another cloud provider or an on-premises solution without significant modifications to your application.
  • Complexity of Debugging
    Debugging and monitoring distributed, serverless applications can be more complex compared to traditional applications due to the lack of direct access to the underlying infrastructure.
  • Cold Start Issues with VPC
    When Lambda functions are configured to access resources within a Virtual Private Cloud (VPC), the cold start latency can be exacerbated due to additional VPC networking overhead.
  • Limited Execution Control
    AWS Lambda is designed for stateless, short-running tasks and may not be suitable for long-running processes or tasks requiring complex orchestration.

Google Cloud Bigtable features and specs

  • Scalability
    Google Cloud Bigtable is designed to scale horizontally to handle massive amounts of data across millions of rows and thousands of columns. This makes it ideal for applications needing to handle large datasets with high throughput.
  • Low Latency
    Bigtable is optimized for low-latency access to big data. It is capable of delivering real-time responses, which is beneficial for applications that require fast read and write operations.
  • Seamless Integration
    Bigtable integrates easily with other GCP services like Google Cloud Storage, BigQuery, and Dataflow, simplifying the development of complex applications that require various cloud services.
  • Managed Service
    As a managed service, Bigtable handles routine operations such as scaling, replication, and failure recovery, allowing users to focus on application development rather than infrastructure management.
  • Strong Consistency
    Bigtable provides strong consistency for read and write operations, ensuring that data is reliable and consistent across operations and query results.

Possible disadvantages of Google Cloud Bigtable

  • Complexity of Use
    Bigtable can be complex to set up and use effectively, especially for those who are unfamiliar with NoSQL databases or distributed systems.
  • Cost
    While scalable, the pricing can become expensive as your requirements grow, especially if you need high throughput and large storage capacities.
  • Limited Querying Capabilities
    Unlike relational databases, Bigtable has limited querying capabilities. It does not support SQL-like queries, making it less suitable for applications that require complex querying options.
  • Region-Specific Availability
    Bigtable is available only in certain regions, which might limit its use for global applications requiring multi-region deployments for latency optimization.
  • Learning Curve
    There's a significant learning curve for new users to understand Bigtable's architecture and its best practices, which can delay the development process.

AWS Lambda videos

AWS Lambda Vs EC2 | Serverless Vs EC2 | EC2 Alternatives

More videos:

  • Tutorial - AWS Lambda Tutorial | AWS Tutorial for Beginners | Intro to AWS Lambda | AWS Training | Edureka
  • Tutorial - AWS Lambda | What is AWS Lambda | AWS Lambda Tutorial for Beginners | Intellipaat

Google Cloud Bigtable videos

Scalability Meetup @ Whitepages - Google Cloud BigTable

Category Popularity

0-100% (relative to AWS Lambda and Google Cloud Bigtable)
Cloud Computing
100 100%
0% 0
Databases
0 0%
100% 100
Cloud Hosting
100 100%
0% 0
NoSQL Databases
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 AWS Lambda and Google Cloud Bigtable

AWS Lambda Reviews

Top 7 Firebase Alternatives for App Development in 2024
AWS Lambda is suitable for applications with varying workloads and those already using the AWS ecosystem.
Source: signoz.io

Google Cloud Bigtable Reviews

7 Best NoSQL APIs
When businesses need to scale, they want to do so with limited downtime. The Google Cloud Bigtable provides horizontal Scaling in a matter of seconds without any downtime. To scale, cluster nodes are quickly added to increase your overall Bigtable cluster. Google even provides the option of scaling out only for a matter of hours, to handle a large load of requests. Once the...

Social recommendations and mentions

Based on our record, AWS Lambda seems to be a lot more popular than Google Cloud Bigtable. While we know about 275 links to AWS Lambda, we've tracked only 6 mentions of Google Cloud Bigtable. 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.

AWS Lambda mentions (275)

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Google Cloud Bigtable mentions (6)

  • Vaultree and AlloyDB: the world's first Fully Homomorphic and Searchable Cloud Encryption Solution
    In my opinion, Google has built some fantastic database services like Bigtable and Spanner, which literally changed the industry for good, and I am eager to see how they will build upon this new service. With AlloyDB's disaggregated architecture, the dystopian world where I only pay for SQL databases per query and the stored data on GCP seems closer than ever. - Source: dev.to / over 2 years ago
  • Google Cloud Reference
    Cloud Bigtable: Petabyte-scale, low-latency, non-relational 🔗Link 🔗Link. - Source: dev.to / over 2 years ago
  • A Graph-Based Firebase
    > These triples say that the Layer with id 1 has a fontSize 20 and backgroundColor blue. Since they are different rows, there’s no conflict. This sounds a lot like Bigtable (https://cloud.google.com/bigtable), which also does last-write-wins conflict resolution layer. So this is adding a GraphQL + frontend layer to it? - Source: Hacker News / over 2 years ago
  • The 4 Types of NoSQL Databases You Need to Know
    Google's BigTable paper inspired this database design, and it is capable of handling large data loads on distributed machines. In addition, column-oriented databases provide efficient compression and high performance with aggregated queries such as sum, average, and minimum. - Source: dev.to / almost 3 years ago
  • Can someone help me understand why data batch processing and data streaming processing pose such different challenges in data management?
    Because of these and other differences, the tools used are also different. With batch processing, data might be read from large files, processed, and stored in an OLTP (Online Transaction Processing) database (like MySQL) or OLAP (Online Analytical Processing) system (like Google BigQuery). But these would not be good solutions for streaming applications, because they are not optimized for high throughput on a lot... Source: over 3 years ago
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What are some alternatives?

When comparing AWS Lambda and Google Cloud Bigtable, you can also consider the following products

Amazon S3 - Amazon S3 is an object storage where users can store data from their business on a safe, cloud-based platform. Amazon S3 operates in 54 availability zones within 18 graphic regions and 1 local region.

MongoDB - MongoDB (from "humongous") is a scalable, high-performance NoSQL database.

Amazon API Gateway - Create, publish, maintain, monitor, and secure APIs at any scale

Amazon Aurora - MySQL and PostgreSQL-compatible relational database built for the cloud. Performance and availability of commercial-grade databases at 1/10th the cost.

Google App Engine - A powerful platform to build web and mobile apps that scale automatically.

Azure Cosmos DB - NoSQL JSON database for rapid, iterative app development.