Sendgrid is a cloud-based email service that allows companies around the world to reliably deliver emails without having to build their own in-house email infrastructure. With Sendgrid, you can build and nurture your customer relationships by sending the right email, to the right people, at the right time.
Amazon Kinesis is a powerful analytics solution that overcomes the batch-processing challenges of Hadoop — and similar solutions — which don't allow real-time precision in decision-making because they can't rapidly process high volumes of streaming data. With its ability to process hundreds of terabytes of streaming data per hour, Kinesis allows you to develop apps that rely on real-time data to fuel AI analytics, machine learning insights, and other applications. Kineses enables instant responses by eliminating the delay associated with batch processing.
Bring all your SendGrid data to Amazon Redshift
Load your SendGrid data to Google BigQuery
ETL all your SendGrid data to Snowflake
Move your SendGrid data to MySQL
Bring all your Amazon Kinesis data to Amazon Redshift
Load your Amazon Kinesis data to Google BigQuery
ETL all your Amazon Kinesis data to Snowflake
Move your Amazon Kinesis data to MySQL
Create, manage, send, and schedule campaigns through Sendgrid. Then, monitor campaign performance and use that data to make any necessary pivots in your marketing strategies.
Specify an email address and receive daily, weekly, or monthly notifications regarding your email usage or stats. Use this information to get big-picture insights about email performance and success rates.
Easily unsubscribe email addresses, ensuring that none of your communication goes to the wrong audience.
Retrieve all of your email statistics within a specific date range. Use this data to monitor campaign performance, email frequency, and other relevant insights.
Tag emails by type or topic, and use this segmentation to send more targeted, precise communication to each of your audiences.
Manage your contacts, segmenting them, creating lists of recipients, adding recipients to specific campaigns, and more. This kind of flexible, targeted communication will not only improve open rates, but also increase customer satisfaction and overall ROI.
Amazon Kineses Video Streams allow you to safely ingest streaming video data from millions of linked devices into AWS for machine learning, analytical, and other processing purposes. The platform then encrypts, stores, and indexes the video data so you can access video with simple APIs, play live video streams, and offer on-demand playback. When incorporating this technology with Amazon Rekognition Video, TensorFlow, ApacheMxNet, and OpenCV, Amazon Kineses Video Streams makes it possible to build video analytics and computer vision processes into your applications.
By capturing, processing, and storing data streams, Amazon Kinesis offers a real-time data streaming solution to ingest large amounts of information from hundreds of thousands — even millions — of sources at the gigabytes-per-second scale. The massive scalability of this solution lets you capture and produce immediate analytics on data pertaining to financial transactions, database event streams, location tracking data, clickstreams, social media activity, and more. Since the availability of streaming data happens in milliseconds, the platform enables real-time analytics of this information for instant detection of anomalies, dynamic price adjustments, precise dashboard metrics, and more.
Amazon Kinesis Data Firehose provides a simple and durable way to pull your streaming data into data warehouses, data lakes, and analytics solutions. Due to its compatibility with Splunk, Amazon Redshift, Amazon S3, and Amazon Elasticsearch Service, Kinesis Data Firehose empowers real-time data analytics for the dashboarding and BI tools you've come to trust. Fully managed and automatically scaling, you can use Firehose to encrypt, batch, transform, and compress your information before ingestion to boost security and save on disk space.
Amazon Kinesis Data Analytics helps users without programming knowledge to analyze data streams with SQL or Java. For team members who know SQL, an SQL editor and templates are available for creating streaming applications or querying streaming data. Meanwhile, those with Java knowledge can develop more nuanced streaming applications that perform real-time data transformations and analytical processes.