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Description
Agile Data Engine serves as a robust DataOps platform crafted to optimize the lifecycle of cloud-based data warehouses, encompassing their development, deployment, and management. This solution consolidates data modeling, transformation processes, continuous deployment, workflow orchestration, monitoring, and API integration into a unified SaaS offering. By leveraging a metadata-driven model, it automates the generation of SQL scripts and the workflows for data loading, significantly boosting efficiency and responsiveness in data operations. The platform accommodates a variety of cloud database systems such as Snowflake, Databricks SQL, Amazon Redshift, Microsoft Fabric (Warehouse), Azure Synapse SQL, Azure SQL Database, and Google BigQuery, thus providing considerable flexibility across different cloud infrastructures. Furthermore, its modular data product architecture and pre-built CI/CD pipelines ensure smooth integration and facilitate ongoing delivery, empowering data teams to quickly adjust to evolving business demands. Additionally, Agile Data Engine offers valuable insights and performance metrics related to the data platform, enhancing overall operational transparency and effectiveness. This capability allows organizations to make informed decisions based on real-time data analytics, further driving strategic initiatives.
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
Amazon Redshift
Apache Doris
Apache Flink
Apache Kafka
Apache Spark
Azure SQL Database
Azure Synapse Analytics
Databricks
Google Cloud BigQuery
Microsoft Fabric
Integrations
Amazon Redshift
Apache Doris
Apache Flink
Apache Kafka
Apache Spark
Azure SQL Database
Azure Synapse Analytics
Databricks
Google Cloud BigQuery
Microsoft Fabric
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
Agile Data Engine
Country
Finland
Website
www.agiledataengine.com
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
Product Features
Data Warehouse
Ad hoc Query
Analytics
Data Integration
Data Migration
Data Quality Control
ETL - Extract / Transfer / Load
In-Memory Processing
Match & Merge