Usecase
Snowflake and Digazu
End-to-end Real-Time Data Integration
From any set of heterogeneous data sources to Snowflake in real-time:
1
Collection
Real-time connectors from most data formats
2
Transformation
Low-code real-time transformations
3
Distribution
Streaming to Snowflake (Snowpipe Streaming)
Transformative Business Impacts
Expanded Real-Time Analytics
Broaden your analytics scope with access to more diverse data sources.
Enhanced Data Governance
Focus on crucial data retention and anonymization, aligning with compliance standards.
Cost Efficiency
Transform data before Snowflake integration to reduce storage costs and achieve significant savings.
Examples of use cases with Digazu and Snowpipe streaming
Snowpipe Streaming revolutionises how data moves from Kafka to Snowflake, offering unparalleled low-latency and efficient data pipelines.
Here are some examples of use-cases you can support with Snow-pipe streaming:
Low-latency telemetry analytics of user-application interactions for clickstream recommendations.
Identification of security issues in real-time streaming log analytics to isolate threats.
Stream processing of information from IoT devices to monitor critical assets.
A full range of real-time connectors
Digazu’s real-time connectors connect to any source type and minimise the ingestion load by using a “read once, use multiple times” approach with incremental ingestion capabilities such as Change Data Capture (CDC).
A full range of real-time connectors
Digazu’s real-time connectors connect to any source type and minimise the ingestion load by using a “read once, use multiple times” approach with incremental ingestion capabilities such as Change Data Capture (CDC).
A full range of real-time connectors
Digazu’s real-time connectors connect to any source type and minimise the ingestion load by using a “read once, use multiple times” approach with incremental ingestion capabilities such as Change Data Capture (CDC).
A full range of real-time connectors
Digazu’s real-time connectors connect to any source type and minimise the ingestion load by using a “read once, use multiple times” approach with incremental ingestion capabilities such as Change Data Capture (CDC).
A full range of real-time connectors
Digazu’s real-time connectors connect to any source type and minimise the ingestion load by using a “read once, use multiple times” approach with incremental ingestion capabilities such as Change Data Capture (CDC).
A full range of real-time connectors
Digazu’s real-time connectors connect to any source type and minimise the ingestion load by using a “read once, use multiple times” approach with incremental ingestion capabilities such as Change Data Capture (CDC).