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What is Actian VectorAI DB?

The Actian VectorAI DB is a highly adaptable vector database designed with a local-first approach, specifically for AI applications that require immediate access to their data, making it ideal for edge, on-premises, and hybrid configurations. This innovative technology allows developers to create solutions that utilize semantic search, retrieval-augmented generation (RAG), and AI functionalities without relying on cloud infrastructure, thus avoiding issues such as latency, dependence on network systems, and costs associated with each query. By featuring native vector storage and optimized similarity search techniques, it utilizes strategies like approximate nearest neighbor indexing and HNSW algorithms, ensuring rapid retrieval from large-scale embedding datasets while maintaining an effective balance between speed and accuracy. Moreover, it is capable of conducting low-latency searches directly on various devices, from typical laptops to smaller platforms like Raspberry Pi, which promotes prompt decision-making and autonomous operations without needing a network connection. In summary, the Actian VectorAI DB not only enhances the efficiency of AI technologies but also provides developers with a robust tool to implement their innovations across a wide range of environments. Its versatility and performance make it a compelling choice for those aiming to leverage AI effectively and independently.

What is Actian Ingres?

Actian Ingres is widely recognized as a highly reliable enterprise transactional database that has evolved into a hybrid solution, offering superior performance in both transactional and analytical processing. By employing a combination of row and column storage formats, it leverages the Vector’s X100 analytics engine to enable fluid transaction processing alongside operational analytics all within a single platform. This database is particularly notable for its dependability, featuring a low total cost of ownership and round-the-clock global support, which has contributed to its reputation for exceptional customer satisfaction. With a rich history of performance, it has empowered numerous organizations to handle billions of transactions over time, skillfully adapting to various deployments and upgrades. As a result, Actian Ingres continues to be a preferred option for enterprises in search of a powerful and efficient database solution. Its commitment to innovation ensures that it remains relevant in an ever-evolving technological landscape.

Media

Media

Integrations Supported

Amazon EKS
Amazon Web Services (AWS)
Azure Kubernetes Service (AKS)
Cohere
Docker
Google Cloud Platform
Google Kubernetes Engine (GKE)
HTML
Hugging Face
Java
JavaScript
Kubernetes
Microsoft Azure
OpenAI
OpenRoad TMS
Python
Raspberry Pi OS
SQL

Integrations Supported

Amazon EKS
Amazon Web Services (AWS)
Azure Kubernetes Service (AKS)
Cohere
Docker
Google Cloud Platform
Google Kubernetes Engine (GKE)
HTML
Hugging Face
Java
JavaScript
Kubernetes
Microsoft Azure
OpenAI
OpenRoad TMS
Python
Raspberry Pi OS
SQL

API Availability

Has API

API Availability

Has API

Pricing Information

Pricing not provided.
Free Trial Offered?
Free Version

Pricing Information

Pricing not provided.
Free Trial Offered?
Free Version

Supported Platforms

SaaS
Android
iPhone
iPad
Windows
Mac
On-Prem
Chromebook
Linux

Supported Platforms

SaaS
Android
iPhone
iPad
Windows
Mac
On-Prem
Chromebook
Linux

Customer Service / Support

Standard Support
24 Hour Support
Web-Based Support

Customer Service / Support

Standard Support
24 Hour Support
Web-Based Support

Training Options

Documentation Hub
Webinars
Online Training
On-Site Training

Training Options

Documentation Hub
Webinars
Online Training
On-Site Training

Company Facts

Organization Name

Actian

Date Founded

1980

Company Location

United States

Company Website

www.actian.com/databases/vectorai-db/

Company Facts

Organization Name

Actian

Date Founded

1980

Company Location

United States

Company Website

www.actian.com/databases/ingres/

Categories and Features

Categories and Features

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