TIBCO Data Virtualization 8 Sets the Standard in Scalability, Performance, and Workload Management
TIBCO Data Virtualization 8 Processes Workloads 5-10 Times Faster with New Massively Parallel Processing Engine
TIBCO Software Inc., a global leader in integration, API management, and analytics, today announced the general availability of TIBCO® Data Virtualization 8 at the AWS re:Invent 2018 conference in Las Vegas, Nevada. The offering is designed to allow businesses and their technology leaders, data engineers, and architects to remove data bottlenecks and implement an agile, high-speed, virtualized data layer in their architecture. Such a layer allows for robust management and governance, while also delivering self-service access to critical data, organizing it for scale, and making it available in a cost-effective manner for applications and analytics.
TIBCO Data Virtualization 8 features a Massively Parallel Processing (MPP) Engine that significantly improves performance by distributing queries across multiple processors, bringing the benefits of data virtualization to modern big data architectures. TIBCO Data Virtualization now includes a MPP Engine as part of its automatic query optimization that improves federated queries across data lakes and relational sources to benefit from the best possible query plan. By scaling data virtualization processing on existing infrastructure, heterogeneous data workloads can be managed with less replication, lower costs, and greater agility. In this way, the solution delivers data virtualization that is up to five to 10 times faster than previous versions without extra engineering.
"Data and insight are the competitive battlegrounds for business today. Organizations that quickly and continuously derive value from data, big and small, will be leaders and others will fall behind," said Brad Hopper, vice president, analytics product strategy, TIBCO. "TIBCO Data Virtualization 8 raises the bar with remarkable advancements in data virtualization, providing a high-performance and agile experience for data engineers, regardless if their task is to provide data to mission-critical applications or help analysts and data scientists discover new data relationships and insights—or both."
The solution's advanced granular workload management sets a new standard for scalability by providing more control over specific server resources, beyond the previously available server or cluster settings. This allows users to control memory usage, request length, row counts, and more, as well as avoid potentially problematic requests so the most important workloads always get prioritized.
TIBCO Data Virtualization 8 turns an enterprise's big data silos into an advantage by easily accessing big data repositories with new data source adapters for Apache Spark™ SQL, Apache Hive, and Apache Impala, and updated adapters for Apache Hive™ and Apache Impala™. TIBCO Data Virtualization 8 further simplifies access with an all-new Elasticsearch adapter.
TIBCO Data Virtualization 8 is newly available on the cloud on Amazon Web Services (AWS) Marketplace. Learn more by visiting https://www.tibco.com/products/data-virtualization.
TIBCO fuels digital business by enabling better decisions and faster, smarter actions through the TIBCO Connected Intelligence Cloud. From APIs and systems to devices and people, we interconnect everything, capture data in real time wherever it is, and augment the intelligence of your business through analytical insights. Thousands of customers around the globe rely on us to build compelling experiences, energize operations, and propel innovation. Learn how TIBCO makes digital smarter at www.tibco.com.
TIBCO and the TIBCO logo are trademarks or registered trademarks of TIBCO Software Inc. and/or its subsidiaries in the United States and/or other countries. Apache, Hive, Impala, and Spark are either registered trademarks or trademarks of The Apache Software Foundation in the United States and other countries. All other product and company names and marks mentioned in this document are the property of their respective owners and are mentioned for identification.