Technical Product Marketing Manager for JBoss Data Grid and JBoss Data Virtualization.
In this role, I'm responsible for creating and delivering technical marketing assets for technical audiences. Focus areas are blogs, videos, or demos for prospective customers. As a Technical Product Marketing Manager, I have technical sales enablement responsibility, including developing technical training materials, demos, and sales tools that are used by solutions architects, consultants, and partner pre-sales teams. Furthermore helping influence the Red Hat JBoss Data Grid and Red Hat JBoss Data Virtualization product direction by internally communicating requirements and opportunities learned through customer interactions.
We're excited to announce the availability of Red Hat JBoss Data Grid (JDG) Version 7.1. Thanks and congratulations to the JDG engineering and product management team for this release. JDG 7.1 release focuses on the following areas: Performance enhancements Apache Spark 2.x integration Several other enhancements The following new features were added in support of these themes: Release Highlights Performance enhancements JDG 7.1 features core performance improvements, especially in clustered write operations. Current tests have shown up to 60% increase...
An in-memory data grid is a distributed data management platform for application data that: Uses memory (RAM) to store information for very fast, low-latency response time, and very high throughput. Keeps copies of that information synchronized across multiple servers for continuous availability, information reliability, and linear scalability. Can be used as distributed cache, NoSQL database, event broker, compute grid, and Apache Spark data store. The technical advantages of an in-memory data grid (IMDGs) provide business benefits in the form of...
Red Hat JBoss Data Virtualization (JDV) provides several capabilities for caching data including: materialized views, result set caching, and code table caching. These techniques can be used to significantly improve performance in many situations. With the exception of external materialized views, the cached data is accessed through the BufferManager. For better performance, the BufferManager setting should be adjusted to the memory constraints of your installation. See the Admin Guide for more on parameter tuning. JDV supports two kinds of caching...
Welcome to another episode of the series: “Unlock your Red Hat JBoss Data Grid (JDG) data with Red Hat JBoss Data Virtualization (JDV).” This post will guide you through an example of connecting to Red Hat JBoss Data Grid data source, using Teiid Designer. In this example, we will demonstrate connecting to a local JDG data source. We’re using the JDG 6.6.1, but you can connect to any local or remote JDG source (version 6.6.1) if you wish, using the...
Welcome to part 4 of Red Hat JBoss Data Virtualization (JDV) running on OpenShift. JDV is a lean, virtual data integration solution that unlocks trapped data and delivers it as easily consumable, unified, and actionable information. JDV makes data spread across physically diverse systems such as multiple databases, XML files, and Hadoop systems appear as a set of tables in a local database. When deployed on OpenShift, JDV enables: Service enabling your data. Bringing data from outside to inside the...
Welcome to part 3 of Red Hat JBoss Data Virtualization (JDV) running on OpenShift. JDV is a lean, virtual data integration solution that unlocks trapped data and delivers it as easily consumable, unified, and actionable information. JDV makes data spread across physically diverse systems such as multiple databases, XML files, and Hadoop systems appear as a set of tables in a local database. When deployed on OpenShift, JDV enables: Service enabling your data Bringing data from outside to inside the...
Welcome to the part 2 of Red Hat JBoss Data Virtualization (JDV) running on OpenShift. JDV is a lean, virtual data integration solution that unlocks trapped data and delivers it as easily consumable, unified, and actionable information. JDV makes data spread across physically diverse systems such as multiple databases, XML files, and Hadoop systems appear as a set of tables in a local database. When deployed on OpenShift, JDV enables: Service enabling your data Bringing data from outside to inside...
Red Hat JBoss Data Virtualization (JDV) is a lean, virtual data integration solution that unlocks trapped data and delivers it as easily consumable, unified, and actionable information. JDV makes data spread across physically diverse systems such as multiple databases, XML files, and Hadoop systems appear as a set of tables in a local database. When deployed on OpenShift, JDV enables: Service enabling your data Bringing data from outside to inside the PaaS Breaking up monolithic data sources virtually for a...
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