Overview
Proprietary architecture with “one-touch” deployment leveraging infrastructure as code and complete cloud resource provisioning
- Modular and scalable for optimal cost and performance
- 90% faster, one-touch setup using infrastructure as code
- Segregated for flexible development
- Secure, compliant by design
- DevSecOps with built-in CI/CD and SCM
Quickly and easily implement data pipelines that optimize industrial data integration and processing.
Antares IDL Benefits
Antares deploys to AWS, Azure or GCP with a single click after initial configuration to reduce the chance of deployment errors and enable quick time to value.
The platform leverages fully mature concepts tested with clients and supports the full application lifecycle, features a data catalog from the start and automates permission management.
Save time and cost
Save development resources while ensuring quicker time to value with extensive automation that eliminates errors typical in manual processes.
Scale and adapt to any use case
Process both structured data coming from traditional SQL databases and semi-/unstructured data ingested from IoT/edge devices, logs and documents without a fixed format.
Ensure security and compliance
Anonymize entire datasets on the fly, use enterprise-grade identity and access management to govern access and empower users to easily configure anonymization requirements.
Optimize performance
Leverage proprietary tools in a modular setup to easily integrate components and ensure faster processing of massive datasets.
Streamline analytics
Incorporate data catalog tools natively to dramatically reduce data discovery times by automating much of the effort in building, maintaining and running ETL jobs.
Antares IDL Components
In addition to offering extensive customization options, the Antares reference architecture includes components that make it ready to deploy for UAT on AWS.
MQTT Deployment to AWS EKS using EMQX
EMQX, a fully open-source MQTT broker, ensures stability, scalability and low latency in messaging, making it an ideal choice for industry 4.0 applications.
Kafka Deployment to AWS MSK
Kafka ensures the ingestion, processing and delivery of real-time, large-scale data streams, forming an integral part of the pipeline.
Kafka Connector to Snowflake
This robust connector provides a smooth channel for data to move from Kafka to Snowflake, promoting easy and comprehensive data analytics.
Snowflake Schema
A foundation for efficient data modeling and manipulation within the Snowflake environment.
Example Data Producer
This producer sends the data through the pipeline, from generation to ingestion in Snowflake, simulating the entire data flow process for better understanding and testing.
Monitoring Tools
Grafana provides comprehensive insights into the processed data, while InfluxDB underpins it as with high-performance data storage specifically for time series data to provide a robust solution for real-time monitoring and analytics.
Learn how Antares IDL can help you break down information silos and enable a better understanding of operations.