Organizations seek ways to reduce data management costs and complexity. Moving, replicating, and transforming data across systems is time-consuming and often results in unsynchronized data stored in multiple silos.
Customers experience greater choice, interoperability, and cost efficiency when using Teradata’s open table formats with open catalog integration—without sacrificing the powerful and scalable engine that differentiates Teradata in its ability to optimize value and business outcomes.
OTFs provide a flexible, cost-efficient, and easy-to-use storage abstraction layer, enabling customers to manage enterprise data with minimal data movement, reduced complexity, and cost.
Teradata’s open and connected approach to supporting OTFs enables cross-read, cross-write, and cross-query of data stored in a variety of OTFs and open catalogs in multi-cloud and multi-data-lake environments.
Explore AI use cases with a future-ready, truly modern data strategy with unmatched agility and flexibility to deliver Trusted AI at scale—all without the need to move, replicate, or transform data.
Teradata VantageCloud and Teradata AI Unlimited include support for open table format (OTF) data stores, expanding customer choice for data storage and management. Teradata offers freedom of choice with first-party support for Apache Iceberg and Delta OTFs, leveraging object stores like AWS S3, Azure Data Lake Storage, and Google Cloud Storage.
OTFs provide a standardized storage abstraction layer that defines the structure and rules for how analytical engines interact with data in object storage. This architecture enables you to maintain a single data store for use by multiple analytical engines and tools without needing to host, replicate, and manage multiple copies of large datasets.
Together with OTFs, VantageCloud and AI Unlimited deliver access to the connected data foundation for Teradata’s industry-leading AI + Knowledge Platform for harmonized data and other key capabilities.
Teradata provides an open ecosystem for OTFs, catalogs, and cloud service providers (CSPs) in multi-cloud and multi-data lake environments.
This unique, open, and connected approach to supporting OTFs enables cross-read, cross-write, and cross-query of data stored in Apache Iceberg and Delta Lake tables using open catalogs such as AWS Glue, Hive Metastore, or Unity.
This future-ready approach allows enterprises to employ a truly modern data strategy, with unmatched agility and flexibility to deliver Trusted AI at scale—all without the need to move, replicate, or transform data.
Externally managed open table formats (OTFs) allow organizations to retain full control over their data architecture while leveraging Teradata’s high-performance capabilities. With native VantageCloud support for high-performance Iceberg reads, Teradata delivers fast, efficient queries directly against customer-managed OTF lakehouses, without requiring infrastructure changes.
Teradata’s OTF implementation optimizes performance for parallel processing of shared data by leveraging world-class features, such as AMP parallelism, cost-based query optimization, and intelligent workload management. This ensures scalable, responsive analytics across large datasets and diverse environments.
Break down queries into smaller components executed in parallel, with dedicated AMP steps handling tasks like data file scanning, manifest processing, and pruning for optimized performance.
Native read capabilities, a powerful cost-based query optimizer, and advanced caching techniques boost query speed and resource efficiency.
Support for predicate retrieves, joins, aggregations, and statistical collections enables complex workloads directly on open formats, minimizing data movement.
Deep integration with VantageCloud’s massively parallel architecture ensures optimized performance and operational efficiency.
Full interoperability with customer-managed open catalogs and multiple query engines promotes interoperability and data sharing, reducing the complexity and cost of data management.
Enterprises can leverage the powerful analytical engines of VantageCloud and AI Unlimited against their own datasets, in their own cloud object stores—enabling an agile approach without the challenge and expense of moving data.
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