Category: Computing & data (Page 1 of 83)

Snowflake announced its modern approach to bring transactional and analytical data together in a single, unified platform with Unistore. Unistore is powered by Hybrid Tables (now available on AWS), a table type that enables fast, high-concurrency point operations to support transactional workloads. With Unistore, customers can simplify their data architectures, while ensuring consistent security and governance across their data. 

As a part of Unistore, Hybrid Tables intelligently identify when a query is transactional or analytical in nature to provide customers with the most optimal query performance. Hybrid Tables run double-digit millisecond point operations alongside users’ analytical queries, all within Snowflake. With Hybrid Tables, organizations can now harness all of their data to unlock various use cases including:

• State Management: Enabling users to maintain application and workflow state in real-time, removing the need to manage multiple database systems.
• Data Serving: Empowering users to serve low-latency data for their apps, without having to move between databases, while maintaining a unified governance and security model.
• Building Lightweight Transactional Apps: Helping users build lightweight transactional apps with Snowflake’s expanded support for transactional capabilities, simplifying both app development and their architectures.

https://www.snowflake.com/en/blog/unistore-general-availability

DataStax, a AI platform, announced the enhancement of its GitHub Copilot extension with its AI Platform-as-a-Service (AI PaaS) solution. This extension makes it easier for developers to directly interact with DataStax Langflow and their Astra DB databases’ vector, tabular, and streaming data right from their IDE (integrated development environment) through the DataStax GitHub Copilot Extension. 

As generative AI adoption accelerates, developers are seeking tools that not only enhance productivity but also simplify complex workflows, enabling them to keep pace with innovation. New features include:

• Database Creation: Developers can create databases (vector or serverless), in the user’s preferred cloud provider and region, in Astra DB directly through GitHub Copilot.
• Flow creation: The Copilot Extension can build Langflow flows using simple English conversational prompts, provide direct links to the flows, and generate API calls to Langflow application endpoints in VSCode.
• Expanded Capabilities: Copilot answers questions about databases and helps troubleshoot queries. These new features address challenges developers face by bringing low-code and traditional developers together, enabling a broader range of experience levels to leverage powerful AI tools within the familiar VS Code environment. This reduces the time to production, especially for teams that need to deliver quickly in competitive environments.

https://www.datastax.com/blog/astra-db-extension-github-copilot-updates

Semantic Web Company and Ontotext today announced the two companies have merged to become Graph AI provider, Graphwise. Semantic Web Company brings expertise in knowledge engineering, semantic AI and intelligent document processing, while Ontotext brings a versatile graph database engine and AI models for linking and unifying information.

Combining Ontotext GraphDB’s data management capabilities with PoolParty, knowledge and content management offerings from Semantic Web Company, Graphwise has created a comprehensive knowledge graph management platform, which includes complete multi-modal data support – unstructured, semi-structured and structured data. The Graphwise Platform, will enable customers to benefit from: 

• Sophisticated, accurate and reliable AI applications that leverage the power of knowledge graphs for applications like Graph RAG, NLP, recommendation systems, and predictive analysis. 
• Support unstructured and semi-structured data management into data fabric processes. 
• The ability to scale effortlessly, while ensuring data remains well-structured and classified. This enables businesses to build AI systems capable of navigating vast networks of interconnected information without sacrificing accuracy or performance. 
• Enhanced flexibility in designing models by providing the tools necessary in one platform to simplify architectural decisions.
• A combined partner ecosystem and a broader market which creates more opportunities, including significantly larger project volumes. 

https://graphwise.ai