TileDB and Snowflake Unite to Power Scientific AI Discovery

CAMBRIDGE, Mass. – December 17, 2025 – In a significant move to bridge the gap between complex scientific research and enterprise analytics, TileDB today announced the launch of TileDB Carrara as a Snowflake Connected App. The new integration creates a unified data intelligence platform designed to break down long-standing data silos, particularly within the demanding healthcare and life sciences sector.

The partnership enables organizations to seamlessly govern and analyze disparate datasets—from intricate genomic and medical imaging files stored in TileDB to structured business data in Snowflake—all through a single interface. This aims to dramatically accelerate the development of sophisticated artificial intelligence models that depend on a complete, holistic view of data.

Shattering the Multimodal Data Barrier

For years, a fundamental challenge has hampered progress in data-intensive fields: fragmentation. Scientific and multimodal data, such as genomics, proteomics, and high-resolution imaging, are often called "unstructured" due to their complexity and have historically required specialized, isolated systems for storage and analysis. Meanwhile, enterprise data, like patient records and clinical trial results, typically resides in powerful, scalable cloud data platforms like Snowflake. This separation creates a significant bottleneck for AI and machine learning initiatives.

"Organizations today struggle with data fragmentation between specialized platforms for complex data and powerful analytics engines," said Stavros Papadopoulos, Founder and CEO of TileDB, in the announcement. "TileDB Carrara minimizes this challenge."

TileDB has built its reputation on an "omnimodal" platform that uses powerful, shape-shifting multi-dimensional arrays to manage complex data types that traditional databases cannot. This array-native architecture is particularly adept at handling the massive datasets common in bioinformatics and medical research, allowing for high-performance slicing and analysis without moving enormous files. The new integration extends this capability directly into the Snowflake ecosystem. Joint customers can now manage and access all their data assets through a single catalog, with automatic credential management and seamless Python integration, accelerating their AI and analytics workflows.

A Unified Engine for End-to-End Analytics

The integration is built on the Snowflake Connected App framework, a model designed to bring applications directly to the customer's data, rather than requiring data to be moved to the application. This architecture ensures that customers retain full control and governance over their sensitive information within their own secure Snowflake instance.

Key to the TileDB Carrara integration are several features designed to streamline workflows for data scientists and researchers. First, a unified catalog automatically registers and displays Snowflake tables alongside TileDB's complex arrays, providing a "single pane of glass" for all data assets. This eliminates the need for users to toggle between systems to locate and manage their information.

Second, the platform automates security and access through RSA Key Pair authentication. This removes the burdensome and error-prone process of manual credential management, allowing developers in TileDB Carrara’s notebook and task graph environments to securely access Snowflake data using the standard Snowflake SDK. The connection details are handled automatically in the background.

This seamless connectivity allows organizations to build powerful, end-to-end machine learning pipelines. For example, a researcher could use TileDB Carrara to slice a massive genomic dataset, join it with tabular clinical trial data from Snowflake, and then feed the combined dataset directly into Snowflake Cortex AI—the platform's fully managed AI service—to train a predictive model. All this can happen within a single, secure, and managed environment.

Revolutionizing Healthcare and Life Sciences Discovery

Nowhere is the potential impact of this unified approach more profound than in healthcare and life sciences (HCLS). The ability to integrate multiomics profiles, clinical imaging, electronic health records, and real-world evidence is considered the holy grail for accelerating drug discovery and advancing personalized medicine.

TileDB is already a proven technology in this domain, with science and data teams at top pharmaceutical and biotech companies using its platform to power their FAIR (Findable, Accessible, Interoperable, and Reusable) data initiatives. For instance, global pharmaceutical giant Boehringer Ingelheim uses TileDB to build its single-cell transcriptomics database, enabling research at an unprecedented scale. Similarly, Quest Diagnostics leveraged the platform to unify its data infrastructure, achieving significant storage cost reductions while improving efficiency.

With the Snowflake integration, these capabilities become even more powerful. A research team could now analyze single-cell data from TileDB to identify a potential drug target and immediately cross-reference it with patient cohort data in Snowflake to assess its clinical relevance. This can drastically shorten research cycles that previously took months of complex data engineering work. The platform supports a wide range of critical HCLS use cases, from structuring large pathology images for cloud-based visualization to enabling large-scale genomic analysis for population health studies.

A Strategic Play in the Evolving Data Cloud

This partnership is also indicative of a broader strategic trend in the data cloud market. Rather than attempting to be a one-size-fits-all solution, major platforms like Snowflake are fostering robust partner ecosystems. They are encouraging specialized vendors like TileDB to build integrated applications that extend the platform's capabilities into niche but critical areas.

"Building solutions that integrate with Snowflake can be transformative for many businesses as they pursue scientific innovation," noted Kelci Miclaus, Head of Life Sciences AI at Snowflake. She highlighted how TileDB’s high-performance storage for complex scientific data complements Snowflake's strengths in metadata management, governance, and AI-enabled outcomes.

This collaborative approach strengthens both companies. TileDB gains access to Snowflake's vast customer base and its powerful analytics and AI engine, while Snowflake enhances its value proposition for the lucrative HCLS vertical by offering a best-in-class solution for multimodal data challenges. For customers, the result is a more comprehensive, integrated solution that reduces complexity and accelerates time to insight. By combining TileDB’s specialized array-native platform with Snowflake's scalable cloud analytics, the partnership offers a compelling vision for the future of data-driven science, where the full spectrum of data is finally brought together to unlock unprecedented discoveries.