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Compare AWS Batch vs. AWS Lambda

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5,356 views|5,149 comparisons
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6,560 views|6,094 comparisons
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Pricing and Cost Advice
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"AWS is slightly more expensive than Azure.""Its pricing is on the higher side.""The price of the solution is reasonable and it is a pay-per-use model. It is very good for cost optimization.""The cost is based on runtime.""The fees are volume-based.""AWS Lambda is inexpensive."

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Top Answer: The user-friendliness of the solution could be improved. If it was easy to run with the same function in other platforms, other environments, that would make it more portable. That would be really… more »
out of 14 in Compute Service
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out of 14 in Compute Service
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Also Known As
Amazon Batch
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AWS Batch enables developers, scientists, and engineers to easily and efficiently run hundreds of thousands of batch computing jobs on AWS. AWS Batch dynamically provisions the optimal quantity and type of compute resources (e.g., CPU or memory optimized instances) based on the volume and specific resource requirements of the batch jobs submitted. With AWS Batch, there is no need to install and manage batch computing software or server clusters that you use to run your jobs, allowing you to focus on analyzing results and solving problems. AWS Batch plans, schedules, and executes your batch computing workloads across the full range of AWS compute services and features, such as Amazon EC2 and Spot Instances.

AWS Lambda is a compute service that lets you run code without provisioning or managing servers. AWS Lambda executes your code only when needed and scales automatically, from a few requests per day to thousands per second. You pay only for the compute time you consume - there is no charge when your code is not running. With AWS Lambda, you can run code for virtually any type of application or backend service - all with zero administration. AWS Lambda runs your code on a high-availability compute infrastructure and performs all of the administration of the compute resources, including server and operating system maintenance, capacity provisioning and automatic scaling, code monitoring and logging. All you need to do is supply your code in one of the languages that AWS Lambda supports (currently Node.js, Java, C# and Python).

You can use AWS Lambda to run your code in response to events, such as changes to data in an Amazon S3 bucket or an Amazon DynamoDB table; to run your code in response to HTTP requests using Amazon API Gateway; or invoke your code using API calls made using AWS SDKs. With these capabilities, you can use Lambda to easily build data processing triggers for AWS services like Amazon S3 and Amazon DynamoDB process streaming data stored in Amazon Kinesis, or create your own back end that operates at AWS scale, performance, and security.

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Sample Customers
Hess, Expedia, Kelloggs, Philips, HyperTrack
Top Industries
Media Company28%
Computer Software Company19%
Comms Service Provider16%
Financial Services Firm8%
Computer Software Company33%
Financial Services Firm25%
Healthcare Company8%
Venture Capital & Private Equity Firm8%
Computer Software Company23%
Media Company20%
Comms Service Provider17%
Financial Services Firm7%
Company Size
No Data Available
Small Business33%
Midsize Enterprise10%
Large Enterprise57%
Find out what your peers are saying about Apache, Amazon, Zadara and others in Compute Service. Updated: October 2021.
541,108 professionals have used our research since 2012.

AWS Batch is ranked 6th in Compute Service while AWS Lambda is ranked 2nd in Compute Service with 16 reviews. AWS Batch is rated 0.0, while AWS Lambda is rated 8.6. On the other hand, the top reviewer of AWS Lambda writes "Programming is getting much easier and does not need a lot of configuration ". AWS Batch is most compared with AWS Fargate, Apache Spark, Oracle Compute Cloud Service, Amazon Elastic Inference and Apache NiFi, whereas AWS Lambda is most compared with Apache NiFi, Apache Spark, Azure Stream Analytics, Apache Storm and Google Cloud Dataflow.

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We monitor all Compute Service reviews to prevent fraudulent reviews and keep review quality high. We do not post reviews by company employees or direct competitors. We validate each review for authenticity via cross-reference with LinkedIn, and personal follow-up with the reviewer when necessary.