Streambased offers a SQL-based analytics service for Apache Kafka that enables real-time querying of event streaming data without complex setup or data movement. This solution addresses the challenge of accessing timely and relevant data for analytics, allowing data scientists and analysts to improve model accuracy and uncover business insights instantly.
Funding
$800K 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
Analyzing data streams in Apache Kafka often requires complex setups and data movement, hindering real-time querying and timely access to relevant data for analytics. This complexity makes it difficult for data scientists and analysts to quickly gain insights and improve model accuracy.
Solution
Streambased A.S.K. provides a SQL-based analytics service for Apache Kafka that enables real-time querying of event streaming data without complex setup, management, or data movement. Users can point A.S.K. at their Kafka data and query it using standard SQL tools. By querying data directly at its Kafka source, Streambased eliminates the need for data replication. The service seamlessly translates Schema Registry schemas into table definitions, ensuring analytical rows map perfectly to operational messages. Standard Kafka client quotas can be used to protect the Kafka cluster from rogue workloads, and Kafka ACLs and RBAC can be transparently re-used in SQL tools for access management.
Target Audience
The primary users are data scientists and analysts who need real-time access to Kafka data for analytics and business insights.
Features
- SQL-based querying of Apache Kafka data streams
- Zero deployment and no signup required
- No data movement; queries data directly at its Kafka source
- Seamless integration with Schema Registry for data structure
- Kafka ACLs and RBAC for access management
- DOS protection via client quotas
- Topic statistics for query optimization
- Pre-aggregation for high performance
- Predicate pushdown to reduce data read from Kafka