Integrate Heroku Connect with Amazon Kinesis
About Heroku Connect
Heroku Connect is a data integration tool that uses bi-directional synchronization between Salesforce and Heroku Postgres to harmonize Postgres data your Salesforce information like contacts, accounts, and custom objects. Heroku connect includes a user-friendly, point-and-click interface so non-tech-savvy users can set up the service in minutes without coding or complicated configuration procedures.
About Amazon Kinesis
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.
Popular Use Cases
Bring all your Heroku Connect data to Amazon Redshift
Load your Heroku Connect data to Google BigQuery
ETL all your Heroku Connect data to Snowflake
Move your Heroku Connect 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
Integrate Heroku Connect With Amazon Kinesis Today
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Heroku Connect's End Points
Heroku Connect Synchronization of Apps Across Heroku and Salesforce
Heroku Connect allows you to build apps with open source stacks, natively integrate the apps with Postgres, and directly sync them with Salesforce. By integrating your Salesforce data with Heroku Postgres, it's easy to combine the power of the Lightning Platform with Heroku. Heroku Connect makes the process of building apps that bring your data and processes to your users as easy as coding in SQL.
Heroku Connect External Objects
Heroku Connect External Objects let you make your Heroku Postgres database information available inside your Salesforce deployment. This empowers you to synchronize your information across both platforms as you create, read, update, and delete data. By creating sophisticated applications inside Heroku and making the app data available to your Salesforce processes, you'll present a seamless experience in Salesforce, while all of your data stays inside Heroku Postgres. Moreover, configuring Heroku-Salesforce integrations for data pertaining to apps, sensors, customers, and products is a simple, point-and-click process that doesn't require any coding skills. Heroku External Objects combined with Salesforce Connect makes it easy to create a seamless experience across all of your business systems.
Heroku Connect Data Security Compliance
Heroku Shield Connect supports the development of applications that share sensitive data with Salesforce while complying with the strictest data security standards. Safely integrate CRM data, Protected Health Information (PHI), Personally Identifiable Information (PII), contact information, account data, and custom objects between Heroku apps and Salesforce. Heroku Shield Connect provides an easy pathway for building advanced applications that need to adhere to the most complicated data security regulations, including HIPAA compliance.
Heroku Connect Easy Application Development and Scaling
Through its compatibility with the most popular stacks and programming languages, Heroku Connect facilitates easy application development. Its add-on ecosystem includes your favorite development tools and databases (like New Relic, Mongo, and Redis) so you can use them with the applications you're creating. Through Heroku's proven infrastructure, which currently supports 26 billion daily transactions for massive consumer websites (such as Upworthy and Bonobo) virtually limitless scaling is available for high volume applications.
Amazon Kinesis's End Points
Amazon Kinesis Video Streams
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.
Amazon Kinesis Data Streams
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
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
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.