DeltaStream is a real-time stream processing platform that utilizes Apache Flink to enable streaming analytics and materialized views for immediate data insights. It addresses the need for efficient monitoring and analysis of large-scale data streams, allowing businesses to detect anomalies and update AI models with minimal latency.
Funding
$25M raised to dateRaised to date based on public sources. This may differ from the amount the company actually raised and is based only on what is publicly available on the internet.
Founders
Product
Problem
Traditional methods of processing and analyzing streaming data often involve complex infrastructure and specialized expertise, creating bottlenecks and delays in extracting real-time insights. Businesses struggle to efficiently monitor large-scale data streams, detect anomalies, and update AI models with minimal latency due to the operational overhead of managing Flink clusters.
Solution
DeltaStream provides a stream processing platform powered by Apache Flink that simplifies real-time analytics and materialized views, enabling immediate data insights without requiring specialized Flink expertise. The platform allows users to develop streaming applications and analyze data on-stream, facilitating real-time ETL and AI/ML model updates with millisecond latency. DeltaStream offers a serverless environment with query-level scaling, eliminating the need for cluster management and reducing operational costs. The platform integrates seamlessly with existing data sources, providing a centralized hub for real-time analytics and data product creation.
Target Audience
DeltaStream targets businesses that need to monitor and analyze large-scale data streams in real-time, including those in IoT, security, and AI/ML, as well as data engineers and analysts seeking to simplify stream processing workflows.
Features
- Serverless architecture that eliminates the need for managing Flink clusters
- Simplified SQL interface for developing streaming applications without Flink knowledge
- Real-time ETL capabilities for transforming and enriching data streams
- Materialized views for querying and analyzing data in real-time
- Scalable infrastructure that automatically adjusts resources based on query load
- Role-Based Access Control (RBAC) for secure data access and sharing
- Anomaly detection for identifying variances in IoT sensor data and other data streams
- Integrations with various data sources through a streaming catalog