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  1. Stackups
  2. Application & Data
  3. Serverless
  4. Serverless Task Processing
  5. AWS Lambda vs Apache Kudu

AWS Lambda vs Apache Kudu

OverviewComparisonAlternatives

Overview

AWS Lambda
AWS Lambda
Stacks26.0K
Followers18.8K
Votes432
Apache Kudu
Apache Kudu
Stacks71
Followers259
Votes10
GitHub Stars828
Forks282

Apache Kudu vs AWS Lambda: What are the differences?

What is Apache Kudu? Fast Analytics on Fast Data. A columnar storage manager developed for the Hadoop platform. A new addition to the open source Apache Hadoop ecosystem, Kudu completes Hadoop's storage layer to enable fast analytics on fast data.

What is AWS Lambda? Automatically run code in response to modifications to objects in Amazon S3 buckets, messages in Kinesis streams, or updates in DynamoDB. AWS Lambda is a compute service that runs your code in response to events and automatically manages the underlying compute resources for you. You can use AWS Lambda to extend other AWS services with custom logic, or create your own back-end services that operate at AWS scale, performance, and security.

Apache Kudu can be classified as a tool in the "Big Data Tools" category, while AWS Lambda is grouped under "Serverless / Task Processing".

"Realtime Analytics" is the top reason why over 7 developers like Apache Kudu, while over 124 developers mention "No infrastructure" as the leading cause for choosing AWS Lambda.

Apache Kudu is an open source tool with 828 GitHub stars and 282 GitHub forks. Here's a link to Apache Kudu's open source repository on GitHub.

Udemy, Delivery Hero SE, and Nubank are some of the popular companies that use AWS Lambda, whereas Apache Kudu is used by HelloFresh, Kaspersky Lab, and Cedato. AWS Lambda has a broader approval, being mentioned in 2179 company stacks & 12298 developers stacks; compared to Apache Kudu, which is listed in 5 company stacks and 51 developer stacks.

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Detailed Comparison

AWS Lambda
AWS Lambda
Apache Kudu
Apache Kudu

AWS Lambda is a compute service that runs your code in response to events and automatically manages the underlying compute resources for you. You can use AWS Lambda to extend other AWS services with custom logic, or create your own back-end services that operate at AWS scale, performance, and security.

A new addition to the open source Apache Hadoop ecosystem, Kudu completes Hadoop's storage layer to enable fast analytics on fast data.

Extend other AWS services with custom logic;Build custom back-end services;Completely Automated Administration;Built-in Fault Tolerance;Automatic Scaling;Integrated Security Model;Bring Your Own Code;Pay Per Use;Flexible Resource Model
-
Statistics
GitHub Stars
-
GitHub Stars
828
GitHub Forks
-
GitHub Forks
282
Stacks
26.0K
Stacks
71
Followers
18.8K
Followers
259
Votes
432
Votes
10
Pros & Cons
Pros
  • 129
    No infrastructure
  • 83
    Cheap
  • 70
    Quick
  • 59
    Stateless
  • 47
    No deploy, no server, great sleep
Cons
  • 7
    Cant execute ruby or go
  • 3
    Compute time limited
  • 1
    Can't execute PHP w/o significant effort
Pros
  • 10
    Realtime Analytics
Cons
  • 1
    Restart time
Integrations
No integrations available
Hadoop
Hadoop

What are some alternatives to AWS Lambda, Apache Kudu?

Apache Spark

Apache Spark

Spark is a fast and general processing engine compatible with Hadoop data. It can run in Hadoop clusters through YARN or Spark's standalone mode, and it can process data in HDFS, HBase, Cassandra, Hive, and any Hadoop InputFormat. It is designed to perform both batch processing (similar to MapReduce) and new workloads like streaming, interactive queries, and machine learning.

Presto

Presto

Distributed SQL Query Engine for Big Data

Azure Functions

Azure Functions

Azure Functions is an event driven, compute-on-demand experience that extends the existing Azure application platform with capabilities to implement code triggered by events occurring in virtually any Azure or 3rd party service as well as on-premises systems.

Google Cloud Run

Google Cloud Run

A managed compute platform that enables you to run stateless containers that are invocable via HTTP requests. It's serverless by abstracting away all infrastructure management.

Amazon Athena

Amazon Athena

Amazon Athena is an interactive query service that makes it easy to analyze data in Amazon S3 using standard SQL. Athena is serverless, so there is no infrastructure to manage, and you pay only for the queries that you run.

Apache Flink

Apache Flink

Apache Flink is an open source system for fast and versatile data analytics in clusters. Flink supports batch and streaming analytics, in one system. Analytical programs can be written in concise and elegant APIs in Java and Scala.

lakeFS

lakeFS

It is an open-source data version control system for data lakes. It provides a “Git for data” platform enabling you to implement best practices from software engineering on your data lake, including branching and merging, CI/CD, and production-like dev/test environments.

Druid

Druid

Druid is a distributed, column-oriented, real-time analytics data store that is commonly used to power exploratory dashboards in multi-tenant environments. Druid excels as a data warehousing solution for fast aggregate queries on petabyte sized data sets. Druid supports a variety of flexible filters, exact calculations, approximate algorithms, and other useful calculations.

Serverless

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.

Google Cloud Functions

Google Cloud Functions

Construct applications from bite-sized business logic billed to the nearest 100 milliseconds, only while your code is running

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