How Teradata Vantage with Native Object Store Decreases Costs, Increases Business Value

The latest release of Teradata Vantage with Native Object Store enables companies to not only drive down costs by leveraging object store technologies, but also improve manageability and drive business insights with the power of Vantage.

Mark Shainman
Mark Shainman
7. September 2020 4 min Lesezeit
Teradata Vantage and Native Object Store.
In the drive to push down costs and modernize their big data environments, many companies are looking to leverage object store technologies, especially in the cloud. With the latest release of Teradata Vantage 2.0 with Native Object Store (NOS), we enable companies to not only drive down costs by leveraging object store technologies, but also improve manageability and drive business insights with the power of Vantage.  

Teradata Vantage Native Object Store
Teradata Vantage’s NOS technology allows users to leverage the analytical power of Teradata Vantage against data in object stores such as Amazon’s S3 or Azure Blob Storage. NOS works by allowing Vantage users to simply set up a foreign table definition that maps to data that exists within an object store bucket.

This allows users to query JSON, CSV, and Parquet format data within object stores just like local data within Teradata Vantage. The query process is dynamic and in real time, allowing the data to be analyzed without the need for it to be loaded and continually persisted in local Teradata Vantage storage. NOS also allows Teradata Vantage users to leverage their existing BI tools and languages. 

Native Object Store Use Cases
The value of leveraging object stores within an analytical environment is in the ability to decrease costs and drive business value. With Teradata Vantage’s NOS, companies are able to leverage the technology for a range of business use cases. The three main ones are data lake exploration, query-able data archive, and data sharing.
  • Data Lake Exploration. An evolution is happening in the data lake space. Companies are moving away from their legacy Hadoop to new modern object store centric environments. Object stores are becoming the main repository for companies’ long-term data containers that enable them to capture, refine, and explore any form of raw data. With Teradata Vantage with NOS, companies can now store this data lake centric data within object stores and leverage the power of the Vantage engine to refine and analyze the data. 
  • A business user or citizen data scientist looking to analyze data lake data such as clickstream data or sensor data can simply execute a single query in Teradata Vantage to access the object store data. A user’s query can access the data, prepare it for analysis, and dynamically join it with existing data within the Teradata Vantage system, all in parallel, at scale. Citizen data scientists can leverage robust analytical functions and machine learning processes on the object store data, enabling them to easily explore data and gain business insights. Vantage’s advanced functions such as path and pattern, sessionize, attribution, scoring functions, data prep functions, and numerous others can now be easily leveraged against object store data lake data.  
  • Data Archiving. Organizations look for low-cost solutions that allow them to easily archive infrequently used data within their relational databases. Archiving this data to a low-cost storage medium is the easy part. The hard part is making the archived data easily accessible when it is needed. Teradata Vantage with NOS allows just that—the ability to archive infrequently used data into low-cost object storage while allowing it to still be accessible to users. To make access to this data as simple and seamless as possible for end users, a view can be created on top of the NOS foreign table definition. The view makes the foreign table definition that maps to the object store data look just like a local regular table within Teradata Vantage. The end user sees the archived data as simply a local Vantage table and accesses it in the exact same manner as local data.  
  • Accessing the archived data will have a slightly different performance profile than the locally stored data, but access is simple and in real time. Because the archived data is viewed as just another table in Teradata Vantage, for an end user looking for a combined view of present and past data, it is as easy as writing a simple SQL statement that joins local data with the archived data. All the analytical power of Teradata Vantage is immediately available and leverageable on the archived data. The power of Teradata Vantage with NOS allows companies to get more value out of their archived data by putting immediate access and the power of deep analytics at users’ fingertips.
  • Data Sharing. There is a need to share data easily between departments within a company and with business partners. The process of sharing data within the relational database world, especially around analytics, traditionally entails numerous copies of the data being shipped around to be analyzed. The ability of Teradata Vantage with NOS to leverage open data formats within object stores (JSON, Parquet, and CSV) facilitates an easy way to share analytical data. Data in these open formats can be analyzed using Teradata Vantage and with other tools within and outside of the company. The object store can become a centralized location for the company and partners to load and share data.  

Company and partner users can leverage tools that exist outside of the Teradata Vantage ecosystem to access the open format data. Open format data access facilitates a broader scope of data sharing across an extensive company and partner analytical ecosystem. Utilizing Teradata Vantage with NOS for data sharing helps decrease data duplication and infrastructure complexity by eliminating the need for multiple copies of data to be shipped around the company or to partners. The ability to centralize and effectively share leads to more accurate data, and it broadens the overall analytical scope and access of the data.   
Unlocking New Possibilities 
By providing seamless access to data within object stores, Teradata has opened a wide array of new possibilities and use cases for data access and analytics. Making data access to object stores seamless and easy, in conjunction with the deep analytical power of Teradata Vantage, can help solve a lot of the problems companies face around their big data and analytical initiatives. Teradata Vantage with NOS can help companies modernize their analytical ecosystem by decreasing complexity, reducing costs, and enabling broader data sharing and usage, which in turn drives greater business insights and business value.

Get Started with Native Object Store
Native object store is now generally available on Teradata Vantage with AWS and Azure. To learn more, watch this webinar to see Vantage product and cloud experts showcase the latest product enhancements and cloud feature release. 

Über Mark Shainman

Mark Shainman is the Program Manager for Teradata’s ecosystem management software Teradata IntelliSphere, as well as Teradata Vantage and competitive programs. As part of Teradata’s analytical ecosystem team, Mark looks after the marketing, education, promotion and strategy-surrounding the uptake and usage of QueryGrid, AppCenter, Data Lab, Ecosystem Manager, Multi -System Viewpoint, Data Stream Architecture, Unity and Data Mover, and Teradata Vantage. Mark also continues to be the global program manager for Teradata’s Competitive programs, covering Oracle, IBM, Netezza and SQL Server migrations as well as cloud migrations and data mart consolidations. He has managed the global aspects of technology, strategy, positioning and sales support surrounding numerous products and programs at Teradata. Prior to joining Teradata, he was a senior research analyst for META Group specializing in database management systems for both online transaction processing and decision-support architectures. Shainman has advised clients on a wide spectrum of database issues, including total-cost-of-ownership analysis, data mart consolidation, disaster recovery, replication, and security, while assisting with core database product comparison and selection.
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