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- Hello and welcome to the Data Engineering Podcast, the show about modern data management
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- Your host is Tobias Macey and today I’m interviewing Yair Weinberger about Alooma, a company providing data pipelines as a service
- How did you get involved in the area of data management?
- What is Alooma and what is the origin story?
- How is the Alooma platform architected?
- I want to go into stream VS batch here
- What are the most challenging components to scale?
- How do you manage the underlying infrastructure to support your SLA of 5 nines?
- What are some of the complexities introduced by processing data from multiple customers with various compliance requirements?
- How do you sandbox user’s processing code to avoid security exploits?
- What are some of the potential pitfalls for automatic schema management in the target database?
- Given the large number of integrations, how do you maintain the
- What are some challenges when creating integrations, isn’t it simply conforming with an external API?
- For someone getting started with Alooma what does the workflow look like?
- What are some of the most challenging aspects of building and maintaining Alooma?
- What are your plans for the future of Alooma?
- From your perspective, what is the biggest gap in the tooling or technology for data management today?
- Convert Media
- Data Integration
- ESB (Enterprise Service Bus)
- ETL (Extract, Transform, Load)
- Microsoft SSIS
- OLAP Cube
- Azure Cloud Storage
- Snowflake DB
- The Log: What every software engineer should know about real-time data’s unifying abstraction by Jay Kreps
- RDBMS (Relational Database Management System)
- SaaS (Software as a Service)
- Change Data Capture
- Google Cloud PubSub
- Amazon Kinesis
- Alooma Code Engine
- Kafka Streams
- PII (Personally Identifiable Information)
- GDPR (General Data Protection Regulation)
- Amazon EMR (Elastic Map Reduce)
- Sequoia Capital
- Lightspeed Investors