Average Ratings 0 Ratings
Average Ratings 0 Ratings
Description
Boost.space is a no-code Agentic Database built to provide AI systems and automations with real-time, structured business context. Instead of relying on disconnected tools and siloed datasets, it centralizes customer, product, and operational information into a synchronized Single Source of Truth. The platform performs continuous two-way data synchronization, keeping systems aligned and eliminating inconsistencies or outdated records. Its built-in AI Fields enrich data at scale by classifying entries, filling missing attributes, translating content, and standardizing formats. Users can power automation workflows on top of this standardized data through integrations with Make, and upcoming support for Zapier and n8n. Through MCP (Model Context Protocol), large language models can directly access live business data, retrieve computed answers, and trigger actions across connected tools. Boost.space enables AI agents to move beyond simple chat interactions and become operational decision-makers. The platform is ISO 27001 and SOC-2 compliant, ensuring enterprise-grade security and regulatory alignment. Businesses across ecommerce, sales, and marketing use it to improve data quality and scale automation without increasing headcount. By turning fragmented information into synchronized context, Boost.space enables true AI execution across the organization.
Description
Dremio provides lightning-fast queries as well as a self-service semantic layer directly to your data lake storage. No data moving to proprietary data warehouses, and no cubes, aggregation tables, or extracts. Data architects have flexibility and control, while data consumers have self-service. Apache Arrow and Dremio technologies such as Data Reflections, Columnar Cloud Cache(C3), and Predictive Pipelining combine to make it easy to query your data lake storage. An abstraction layer allows IT to apply security and business meaning while allowing analysts and data scientists access data to explore it and create new virtual datasets. Dremio's semantic layers is an integrated searchable catalog that indexes all your metadata so business users can make sense of your data. The semantic layer is made up of virtual datasets and spaces, which are all searchable and indexed.
API Access
Has API
Yes
API Access
Has API
No
Integrations
Microsoft Power BI
Yes
Tableau
Yes
Apache Iceberg
No
Asana
Yes
Codd AI
No
DataClarity Unlimited Analytics
No
Discord
Yes
Facebook
Yes
Google Drive
Yes
HubSpot CRM
Yes
Integrations
Microsoft Power BI
Yes
Tableau
Yes
Apache Iceberg
Yes
Asana
No
Codd AI
Yes
DataClarity Unlimited Analytics
Yes
Discord
No
Facebook
No
Google Drive
No
HubSpot CRM
No
Pricing Details
$15/month
Free Trial
Yes
Free Version
Yes
Pricing Details
No price information available.
Free Trial
No
Free Version
No
Deployment
Web-Based
Yes
On-Premises
No
iPhone App
No
iPad App
No
Android App
No
Windows
No
Mac
No
Linux
No
Chromebook
No
Deployment
Web-Based
Yes
On-Premises
No
iPhone App
No
iPad App
No
Android App
No
Windows
No
Mac
No
Linux
No
Chromebook
No
Customer Support
Business Hours
No
Live Rep (24/7)
No
Online Support
Yes
Customer Support
Business Hours
No
Live Rep (24/7)
No
Online Support
No
Types of Training
Training Docs
Yes
Webinars
No
Live Training (Online)
No
In Person
No
Types of Training
Training Docs
No
Webinars
No
Live Training (Online)
No
In Person
No
Vendor Details
Company Name
Boost.space
Founded
2017
Country
Czech Republic
Website
boost.space/
Vendor Details
Company Name
Dremio
Founded
2015
Country
United States
Website
www.dremio.com
Product Features
Database
Backup and Recovery
No
Creation / Development
No
Data Migration
No
Data Replication
No
Data Search
No
Data Security
No
Database Conversion
No
Mobile Access
No
Monitoring
No
NOSQL
No
Performance Analysis
No
Queries
No
Relational Interface
No
Virtualization
No
Product Features
Big Data
Collaboration
No
Data Blends
No
Data Cleansing
No
Data Mining
No
Data Visualization
No
Data Warehousing
No
High Volume Processing
No
No-Code Sandbox
No
Predictive Analytics
No
Templates
No
Data Lineage
Database Change Impact Analysis
No
Filter Lineage Links
No
Implicit Connection Discovery
No
Lineage Object Filtering
No
Object Lineage Tracing
No
Point-in-Time Visibility
No
User/Client/Target Connection Visibility
No
Visual & Text Lineage View
No
Data Warehouse
Ad hoc Query
No
Analytics
No
Data Integration
No
Data Migration
No
Data Quality Control
No
ETL - Extract / Transfer / Load
No
In-Memory Processing
No
Match & Merge
No