We have ARRIVED!
We have ARRIVED!
February 17, 2015 is a date that everyone at StreamAnalytix will treasure. It is the day when StreamAnalytix announced its General Availability! This milestone for StreamAnalytix comes after strong validation from our Beta customers and equally strong support from our growing eco-system of technology partners.
The competitive landscape for streaming analytics platforms is growing every week with new entrants announcing products or funding, but our experience with our customers and their feedback informs us that StreamAnalytix stands tall and distinct.
To start with, StreamAnalytix is the ONLY commercially supported and viable streaming analytics platform today based on Open Source technologies. Our value proposition of “Enterprise class on Open Source” is being strongly validated by customers acknowledging how far our platform takes them beyond just a set of Open Source components stitched together. Some of these value-adds and features that customers appreciate are:
- Rapid, easy application development and deployment with a series of pre-built operators
- Visual monitoring of real-time streaming applications with performance based alerts
- Complex event processing integrated on streaming data (get going with no coding or scripting)
- Seamless integration modern data platforms
- Integration of a powerful real-time dash-boarding engine to visualize streaming data
All of these, along with the intuitive and powerful user interface makes it really easy and fast for enterprises to go live with their much-awaited real-time stream processing use-cases in a matter of days or at most a few weeks if there is significant custom application development to be done. The acceleration is so tangible and valuable, and add to that… everything underneath is familiar and proven Open Source technology – that enterprises are finding it hard to say NO to StreamAnalytix. We have also decided to bring in support for Spark streaming later this year so that customers don’t need to choose between Storm and Spark and they have both options supported when they go with our platform.
The use cases we are enabling in various projects are in areas including Internet-of-Things (IoT), sensor data analytics, e-commerce and Internet advertising, security, fraud, insurance claim validation, credit-line-management, call center analytics, and log analytics. Additionally, a common pattern that we are noticing is enterprise IT and business transformation with our Streaming ETL capability that speeds up slow batch processes to near-real-time. We will also announce a partner in the streaming ETL domain soon.
We have certified our product with MapR and Hortonworks with a third, i.e., Cloudera coming soon. The certifications help but it is important to note that we work with any modern data platforms quite naturally simply because of the way we have built our data abstraction layer. It’s the same reason why we work seamlessly with other NoSQL databases like Apache Cassandra. We have even integrated with Mark Logic, another commercial NoSQL database – in about two weeks for a specific customer.
All things considered (including cost) – we feel StreamAnalytix is really the best choice for enterprises wanting to develop and deploy real-time streaming applications quickly and have their batch, speed and service layers tightly integrated. We will be glad to engage, show demos, and have a Q&A session with you if you are considering or evaluating streaming analytics platforms.