Question: Can you recommend a database extension that offers native AI vector processing and analytics lakehouse capabilities?

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EDB Postgres AI

If you want a powerful database extension with native AI vector processing and analytics lakehouse abilities, EDB Postgres AI is a good option. It runs transactional, analytical and AI workloads on the Postgres database engine, providing unified observability and hybrid data management. With features like AI-driven copilots, automation, high availability and performance, it's geared for companies that want to boost their AI and analytics in their Postgres-based workloads.

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Databricks

Another top contender is Databricks, a data intelligence platform that marries generative AI with lakehouse architecture for a unified data foundation. It supports many tools for data ingestion, business intelligence and AI, and democratizes insights with an economical design. Databricks is built on an open, scalable foundation, making it good for many users and use cases, and it offers support, training and community involvement.

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DataStax

If you want a vector database with high-performance abilities, DataStax offers Astra DB, which can handle both vector and structured data. Its Relevant GenAI and Fast Path to Production features make it a good choice for getting generative AI apps into production as fast as possible. With tight integrations and a pay-as-you-go pricing model, DataStax is good for small or large projects.

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Vespa

Last, Vespa is another contender that marries AI with big data, with vector search, lexical search and search in structured data. Its machine-learned model inference is fast and scalable, and its auto-elastic data management means it's fast and low latency. Vespa spans a variety of use cases, including search, recommendation and personalization, so it's good for AI tasks.

Additional AI Projects

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Pinecone

Scalable, serverless vector database for fast and accurate search and retrieval of similar matches across billions of items in milliseconds.

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Qdrant

Scalable vector search engine for high-performance similarity search, optimized for large-scale AI workloads with cloud-native architecture and zero-downtime upgrades.

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Xata

Serverless Postgres environment with auto-scaling, zero-downtime schema migrations, and AI integration for vector embeddings and personalized experiences.

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Teradata

Unifies and harmonizes all data across an organization, providing transparency and speed, and enabling faster innovation and collaboration.

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SingleStore

Combines transactional and analytical capabilities in a single engine, enabling millisecond query performance and real-time data processing for smart apps and AI workloads.

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Elastic

Combines search and AI to extract meaningful insights from data, accelerating time to insight and enabling tailored experiences.

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Vectorize

Convert unstructured data into optimized vector search indexes for fast and accurate retrieval augmented generation (RAG) pipelines.

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Neum AI

Build and manage data infrastructure for Retrieval Augmented Generation and semantic search with scalable pipelines and real-time vector embeddings.

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Couchbase

Unlocks high-performance, flexible, and cost-effective AI-infused applications with a memory-first architecture and AI-assisted coding.

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Dataiku

Systemize data use for exceptional business results with a range of features supporting Generative AI, data preparation, machine learning, MLOps, collaboration, and governance.

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DataRobot AI Platform

Centralize and govern AI workflows, deploy at scale, and maximize business value with enterprise monitoring and control.

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SAS Viya

Streamlines data integration, model development, and cloud cost management, enabling customers to make better decisions with advanced analytics and AI capabilities.

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Neo4j

Analyze complex data with a graph database model, leveraging vector search and analytics for improved AI and ML model performance at scale.

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Airbyte

Seamlessly integrate data from 300+ sources to destinations, with features like custom connector building, unstructured data extraction, and automated schema evolution.

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H2O.ai

Combines generative and predictive AI to accelerate human productivity, offering flexible foundation for business needs with cost-effective, customizable solutions.

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Dataloop

Unify data, models, and workflows in one environment, automating pipelines and incorporating human feedback to accelerate AI application development and improve quality.

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Abacus.AI

Build and deploy custom AI agents and systems at scale, leveraging generative AI and novel neural network techniques for automation and prediction.

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VectorShift

Build and deploy AI-powered applications with a unified suite of no-code and code tools, featuring drag-and-drop components and pre-built pipelines.

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Anyscale

Instantly build, run, and scale AI applications with optimal performance and efficiency, leveraging automatic resource allocation and smart instance management.

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Chat2DB

Simplifies data management with AI-driven features for intelligent SQL development, data exploration, and report generation, making it accessible to all users.