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  5. Amazon Kinesis vs Sift Science

Amazon Kinesis vs Sift Science

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Overview

Amazon Kinesis
Amazon Kinesis
Stacks794
Followers604
Votes9
Sift Science
Sift Science
Stacks14
Followers15
Votes0

Amazon Kinesis vs Sift Science: What are the differences?

Amazon Kinesis: Store and process terabytes of data each hour from hundreds of thousands of sources. Amazon Kinesis can collect and process hundreds of gigabytes of data per second from hundreds of thousands of sources, allowing you to easily write applications that process information in real-time, from sources such as web site click-streams, marketing and financial information, manufacturing instrumentation and social media, and operational logs and metering data; Sift Science: Fight fraud with real time machine learning. Integrate in an afternoon. Sift Science catches fraud by using large-scale machine learning to identify those patterns automatically.

Amazon Kinesis belongs to "Real-time Data Processing" category of the tech stack, while Sift Science can be primarily classified under "Fraud Detection as a Service".

Some of the features offered by Amazon Kinesis are:

  • Real-time Processing- Amazon Kinesis enables you to collect and analyze information in real-time, allowing you to answer questions about the current state of your data, from inventory levels to stock trade frequencies, rather than having to wait for an out-of-date report.
  • Easy to use- You can create a new stream, set the throughput requirements, and start streaming data quickly and easily. Amazon Kinesis automatically provisions and manages the storage required to reliably and durably collect your data stream.
  • High throughput. Elastic.- Amazon Kinesis seamlessly scales to match the data throughput rate and volume of your data, from megabytes to terabytes per hour. Amazon Kinesis will scale up or down based on your needs.

On the other hand, Sift Science provides the following key features:

  • Reduce manual reviews & chargebacks
  • Detect Fraud Automatically in Real-Time
  • Distill Patterns From Data

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Detailed Comparison

Amazon Kinesis
Amazon Kinesis
Sift Science
Sift Science

Amazon Kinesis can collect and process hundreds of gigabytes of data per second from hundreds of thousands of sources, allowing you to easily write applications that process information in real-time, from sources such as web site click-streams, marketing and financial information, manufacturing instrumentation and social media, and operational logs and metering data.

Sift Science catches fraud by using large-scale machine learning to identify those patterns automatically.

Real-time Processing- Amazon Kinesis enables you to collect and analyze information in real-time, allowing you to answer questions about the current state of your data, from inventory levels to stock trade frequencies, rather than having to wait for an out-of-date report;Easy to use- You can create a new stream, set the throughput requirements, and start streaming data quickly and easily. Amazon Kinesis automatically provisions and manages the storage required to reliably and durably collect your data stream;High throughput. Elastic.- Amazon Kinesis seamlessly scales to match the data throughput rate and volume of your data, from megabytes to terabytes per hour. Amazon Kinesis will scale up or down based on your needs;Integrate with Amazon S3, Amazon Redshift, and Amazon DynamoDB- With Amazon Kinesis, you can reliably collect, process, and transform all of your data in real-time before delivering it to data stores of your choice, where it can be used by existing or new applications. Connectors enable integration with Amazon S3, Amazon Redshift, and Amazon DynamoDB;Build Kinesis Applications- Amazon Kinesis provides developers with client libraries that enable the design and operation of real-time data processing applications. Just add the Amazon Kinesis Client Library to your Java application and it will be notified when new data is available for processing;Low Cost- Amazon Kinesis is cost-efficient for workloads of any scale. You can pay as you go, and you’ll only pay for the resources you use. You can get started by provisioning low throughput streams, and only pay a low hourly rate for the throughput you need
Reduce manual reviews & chargebacks;Detect Fraud Automatically in Real-Time;Distill Patterns From Data;Billing & Shipping Address Mismatch;Device Fingerprint;Travel Velocity
Statistics
Stacks
794
Stacks
14
Followers
604
Followers
15
Votes
9
Votes
0
Pros & Cons
Pros
  • 9
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Cons
  • 3
    Cost
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What are some alternatives to Amazon Kinesis, Sift Science?

Google Cloud Dataflow

Google Cloud Dataflow

Google Cloud Dataflow is a unified programming model and a managed service for developing and executing a wide range of data processing patterns including ETL, batch computation, and continuous computation. Cloud Dataflow frees you from operational tasks like resource management and performance optimization.

Tirreno

Tirreno

Open security analytics. Understand, monitor, and protect your product from cyber threats, account takeovers, fake accounts, and abuse.

IPIntel.ai — AI-Powered IP Threat Scoring & Global Intelligence

IPIntel.ai — AI-Powered IP Threat Scoring & Global Intelligence

Real-time IP threat scoring, subnet intelligence, AI-powered analysis and global cyber activity tracking. Fastest IP reputation API.

DMARC Monitoring for Better Email Security

DMARC Monitoring for Better Email Security

Protect your domain with Dmarclytics. Run free DMARC, SPF, and DKIM checks to stop spoofing, enhance email authentication, and improve deliverability with powerful monitoring tools.

Amazon Kinesis Firehose

Amazon Kinesis Firehose

Amazon Kinesis Firehose is the easiest way to load streaming data into AWS. It can capture and automatically load streaming data into Amazon S3 and Amazon Redshift, enabling near real-time analytics with existing business intelligence tools and dashboards you’re already using today.

ThisData

ThisData

We use behavioral patterns to build an identity profile for each user. This provides your app with a second factor of authentication that doesn't add friction to the user experience, or even require the user to opt-in.

Preventor.io

Preventor.io

It is the next generation self-service digital identity and fraud prevention collaborative platform for individuals, businesses, and governments.

Trench

Trench

It is an open source fraud prevention for marketplaces. It is the backbone for your fraud system, bringing all of your data and processes into one place.

Twister2

Twister2

It is a high-performance data processing framework with capabilities to handle streaming and batch data. It can leverage high-performance clusters as well we cloud services to efficiently process data.

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