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Apache Kafka is a distributed event store and stream-processing platform. It is an open-source system developed by the Apache Software Foundation written in Java and Scala . The project aims to provide a unified, high-throughput, low-latency platform for handling real-time data feeds.
Amazon Kinesis is a family of services provided by Amazon Web Services (AWS) for processing and analyzing real-time streaming data at a large scale. Launched in November 2013, it offers developers the ability to build applications that can consume and process data from multiple sources simultaneously. [2]
Confluent, Inc. is an American technology company headquartered in Mountain View, California.Confluent was founded by Jay Kreps, Jun Rao and Neha Narkhede on September 23, 2014, in order to commercialize an open-source streaming platform Apache Kafka, created by the same founders while working at LinkedIn in 2008 as a B2B infrastructure company.
Presto (including PrestoDB, and PrestoSQL which was re-branded to Trino) is a distributed query engine for big data using the SQL query language. Its architecture allows users to query data sources such as Hadoop, Cassandra, Kafka, AWS S3, Alluxio, MySQL, MongoDB and Teradata, [1] and allows use of multiple data sources within a query.
CloudStack is open-source Infrastructure-as-a-Service cloud computing software for creating, managing, and deploying infrastructure cloud services.It uses existing hypervisor platforms for virtualization, such as KVM, VMware vSphere, including ESXi and vCenter, XenServer/XCP and XCP-ng.
Amazon launches Amazon Elastic Compute Cloud (EC2), which forms a central part of Amazon.com's cloud-computing platform, Amazon Web Services (AWS), by allowing users to rent virtual computers on which to run their own computer applications. The service initially includes machines (instances) available for 10 cents an hour, and is available only ...
Amazon Web Services, Inc. (AWS) is a subsidiary of Amazon that provides on-demand cloud computing platforms and APIs to individuals, companies, and governments, on a metered, pay-as-you-go basis. Clients will often use this in combination with autoscaling (a process that allows a client to use more computing in times of high application usage ...
Regardless of which level of abstraction is used, a developer can connect their SageMaker-enabled ML models to other AWS services, such as the Amazon DynamoDB database for structured data storage, [9] AWS Batch for offline batch processing, [9] [10] or Amazon Kinesis for real-time processing.