Striim Reviews & Pricing

Key Features

• Operational Analytics: Leverage custom dashboards to gauge data flows such as table volume metrics and send alerts on data-driven scenarios. Incorporate machine learning capabilities to provide deep insights into real-time data. 
• High Availability: Use built-in recovery functions to ensure exactly-once or at-least-once processing (E1P/ A1P) for critical data flows. Run clusters to support high-availability scenarios where applications can rely on other nodes to ensure zero downtime during issues. 
• SQL-based Transformations: Facilitate real-time data processing and ETL through SQL-based transformations. From filtering data with WHERE clauses to combining data with JOINS, SQL queries run in-memory while converting real-time data ingested by the connectors into the required form. 
• Data Connectors: Use robust connectors to access databases, messaging and file systems, cloud applications, sensors and more. The connectors enable initial loads and ongoing change delivery in a heterogeneous manner. 
• In-flight Transformations: Filter, mask, aggregate, transform and enrich data during motion through out-of-the-box transformers and in-memory stream processing capabilities. Make data consumable for end users using SQL-based queries. 
• Heterogeneous Integration: Merge real-time transactional data from OLTP systems with log data, sensor data, messaging systems and more to obtain comprehensive and reliable business information. 

Limitations

•  Lacks an intuitive web interface. 
•  Limited dashboard capabilities. 
•  Expensive license. 
•  Lacks robust documentation. 

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