Splice Machine Announces Cloud Deployment Containers to Facilitate the Deployment of Intelligent, Mission-Critical Applications on its AWS-Powered Cloud Database
Scale-out cloud data solution enables easy migration of existing applications to the cloud with new AI/ML extensions
SAN FRANCISCO – April 4, 2018 – Splice Machine, provider of a leading data solution to power intelligent applications, today announced that it will be on-site at AWS Summit San Francisco to discuss how its new Cloud Deployment Containers are designed to make it easy for companies to deploy intelligent, mission-critical applications on Amazon Web Services (AWS). The Splice Machine team will be at booth 1117 in Moscone West.
Splice Machine’s Cloud Deployment Containers were designed to greatly facilitate the injection of intelligence into mission-critical cloud applications. This new deployment method allows developers to locally develop Internet of Things (IoT) and artificial intelligence (AI) applications that use streaming and machine learning (ML) technologies on their laptops, and then seamlessly deploy their ML models as containers on a virtual private network with Splice Machine’s Cloud Service. By deploying the same containerized code to the cloud, companies can easily train, test, and deploy machine learning at scale in mission-critical production applications. This deployment capability enables Apache MLlib pipelines to be deployed as containers as well as Spark Streaming applications that can transactionally stream directly into Splice Machine.
With Splice Machine Cloud Deployment Containers, standard applications written in traditional programming languages such as Java or newer languages such as Python, Node, or Scala can be easily migrated to the cloud and then extended with streaming and machine learning.
This enables companies to deploy smarter, predictive applications quickly and easily on the cloud and generate business and customer value in various use cases and verticals, such as supply chain, field service, healthcare, fraud detection and more.
Splice Machine already allows companies to easily migrate on-premises relational database management system (RDBMS) applications at great scale to the cloud as a full ANSI SQL RDBMS and Data Warehouse in one. Customers already realize single record lookups and updates in a few milliseconds at petabyte scale. Additionally, Splice Machine’s analytical capabilities enable extreme analytical concurrency, even at billions of records, with standard connectivity to BI tools such as Tableau and MicroStrategy.
See demos of ML and Streaming applications at booth 1117. For more information on Splice Machine, visit www.splicemachine.com. To schedule a meeting with Splice Machine at the AWS Summit, contact email@example.com.
About Splice Machine
Splice Machine is a new data platform for digital transformation. Unlike other Big Data platforms that provide offline, batch analysis, Splice Machine powers intelligent applications that are woven into the operational workflows of companies. It is a scale-out SQL RDBMS, data warehouse and machine learning platform in one. Splice Machine is open source and is built upon the popular Apache Hadoop, HBase, and Spark distributed platforms. Companies in financial services, healthcare, retail, manufacturing and logistics deploy Splice Machine to improve their operational efficiency, eliminate unnecessary costs and deliver superior service. The Splice Machine database can be deployed on-premise or as a fully-managed cloud service.
Splice Machine is a trademark of Splice Machine, Inc. All other trademarks are the property of their respective registered owners. Trademark use is for identification only and does not imply sponsorship, affiliation, or endorsement.