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the current state of your data, from inventory levels to stock trade frequencies, rather than having to wait for an out-of-date report.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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