Category: Analytics

helps you to reliably process and move data between compute and storage services running either on on on-premises. The pipelines that you create with Data Pipeline’s graphical editor are scalable and fault tolerant, and can be scheduled to run at specific intervals. To learn more, read my launch post, The New AWS Data Pipeline. New […]

We want to make it even easier for you to build applications that run in the . We want you to be able to focus on your code, and to work within a cloud-centric environment where scalability, reliability, and runtime efficiency are all high enough to be simply taken for granted! Today we are launching […]

My colleague Rahul Patil sent me a nice guest post. In the post Rahul shows you how to use the new Kinesis Client Library (KCL) for Python developers. — Jeff; The Amazon Kinesis team is excited to release the Kinesis Client Library (KCL) for Python developers! Developers can use the KCL to build distributed applications […]

My colleague Rahul Patil wrote a guest post to show you how to build an application that loads streaming data from into an Elasticsearch cluster in real-time. — Jeff; The team is excited to release the Kinesis connector to Elasticsearch! Using the connector, developers can easily write an application that loads streaming data from Kinesis […]

I’ve got a special treat for you today! Kiyoto Tamura of Treasure Data wrote a really interesting guest post to introduce you to Fluentd and to show you how you can use it with a wide variety of AWS services to collect, store, and process data. — Jeff; Data storage is Cheap. Data collection is […]

Amazon Kinesis is a real-time service for processing streaming data at massive scale. You can process Kinesis data in a variety of ways, including the Kinesis Client Library, Apache Storm, or Elastic Map Reduce. Mobile gaming companies like Supercell ( AWS Case Study) and analytics companies like Snowplow Analytics ( AWS Case Study) accelerate their […]

The AWS Data Pipeline lets you automate the movement and processing of any amount of data using data-driven workflows and built-in dependency checking. Today we are making the Data Pipeline more flexible and more useful with the addition of a new scheduling model that works at the level of an entire pipeline. This builds upon […]

Two of the most frequent feature requests for Amazon DynamoDB involve backup/restore and cross-Region data transfer. Today we are addressing both of these requests with the introduction of a pair of scalable tools (export and import) that you can use to move data between a DynamoDB table and an Amazon S3 bucket. The export and […]

As we often do, we launched AWS Data Pipeline in a single AWS Region (US East (Northern Virginia) to be precise). It is now available in the following Regions as well: US West (Oregon) EU (Ireland) Asia Pacific (Sydney) Asia Pacific (Tokyo) AWS Data Pipeline has always supported data flows between Regions. With today’s release, […]

Regular readers of this blog already know that Amazon Kinesis is a fully managed service for real-time processing of streaming data at massive scale. As I noted last month when we introduced the Kinesis Storm Spout, Kinesis is but one component of a complete end-to-end streaming data application. In order to build such an application, […]