Average Ratings 0 Ratings
Average Ratings 0 Ratings
Description
Firebolt offers incredible speed and flexibility to tackle even the most daunting data challenges. By completely reimagining the cloud data warehouse, Firebolt provides an exceptionally rapid and efficient analytics experience regardless of scale. This significant leap in performance enables you to process larger datasets with greater detail through remarkably swift queries. You can effortlessly adjust your resources to accommodate any workload, volume of data, and number of simultaneous users. At Firebolt, we are committed to making data warehouses far more user-friendly than what has traditionally been available. This commitment drives us to simplify processes that were once complex and time-consuming into manageable tasks. Unlike other cloud data warehouse providers that profit from the resources you utilize, our model prioritizes transparency and fairness. We offer a pricing structure that ensures you can expand your operations without incurring excessive costs, making our solution not only efficient but also economical. Ultimately, Firebolt empowers organizations to harness the full potential of their data without the usual headaches.
Description
VeloDB, which utilizes Apache Doris, represents a cutting-edge data warehouse designed for rapid analytics on large-scale real-time data.
It features both push-based micro-batch and pull-based streaming data ingestion that occurs in mere seconds, alongside a storage engine capable of real-time upserts, appends, and pre-aggregations. The platform delivers exceptional performance for real-time data serving and allows for dynamic interactive ad-hoc queries.
VeloDB accommodates not only structured data but also semi-structured formats, supporting both real-time analytics and batch processing capabilities. Moreover, it functions as a federated query engine, enabling seamless access to external data lakes and databases in addition to internal data.
The system is designed for distribution, ensuring linear scalability. Users can deploy it on-premises or as a cloud service, allowing for adaptable resource allocation based on workload demands, whether through separation or integration of storage and compute resources.
Leveraging the strengths of open-source Apache Doris, VeloDB supports the MySQL protocol and various functions, allowing for straightforward integration with a wide range of data tools, ensuring flexibility and compatibility across different environments.
API Access
Has API
API Access
Has API
Integrations
Apache Doris
Apache Flink
Apache Kafka
Apache Spark
Embeddable
Hevo
Latitude
Looker
MySQL
Paradime
Integrations
Apache Doris
Apache Flink
Apache Kafka
Apache Spark
Embeddable
Hevo
Latitude
Looker
MySQL
Paradime
Pricing Details
No price information available.
Free Trial
Free Version
Pricing Details
No price information available.
Free Trial
Free Version
Deployment
Web-Based
On-Premises
iPhone App
iPad App
Android App
Windows
Mac
Linux
Chromebook
Deployment
Web-Based
On-Premises
iPhone App
iPad App
Android App
Windows
Mac
Linux
Chromebook
Customer Support
Business Hours
Live Rep (24/7)
Online Support
Customer Support
Business Hours
Live Rep (24/7)
Online Support
Types of Training
Training Docs
Webinars
Live Training (Online)
In Person
Types of Training
Training Docs
Webinars
Live Training (Online)
In Person
Vendor Details
Company Name
Firebolt Analytics
Founded
2019
Country
Israel
Website
firebolt.io
Vendor Details
Company Name
VeloDB
Founded
2023
Country
Singapore
Website
www.velodb.io
Product Features
Data Warehouse
Ad hoc Query
Analytics
Data Integration
Data Migration
Data Quality Control
ETL - Extract / Transfer / Load
In-Memory Processing
Match & Merge
Database
Backup and Recovery
Creation / Development
Data Migration
Data Replication
Data Search
Data Security
Database Conversion
Mobile Access
Monitoring
NOSQL
Performance Analysis
Queries
Relational Interface
Virtualization
Product Features
Data Warehouse
Ad hoc Query
Analytics
Data Integration
Data Migration
Data Quality Control
ETL - Extract / Transfer / Load
In-Memory Processing
Match & Merge