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Welcome to Cortex Data Framework
Section titled “Welcome to Cortex Data Framework”Welcome to the Future of Real-Time Data Processing!
Section titled “Welcome to the Future of Real-Time Data Processing!”We’re thrilled to have you explore Cortex Data Framework — a cutting-edge SDK designed to transform the way developers create and manage real-time data pipelines. Whether you’re a seasoned developer or just starting with stream processing, Cortex offers a simple yet powerful way to handle data at scale.
What is Cortex Data Framework?
Section titled “What is Cortex Data Framework?”The Cortex Data Framework is a powerful, modular, and developer-friendly SDK designed to streamline the creation and management of real-time data processing pipelines. Built with scalability, efficiency, and extensibility in mind, Cortex empowers developers to build complex data streaming applications while abstracting low-level details.
With Cortex, you can focus on crafting robust pipelines that transform, aggregate, and analyze data in real-time, without getting bogged down by the intricacies of state management, concurrency, or integration.
Key Features
Section titled “Key Features”-
Stream Processing Simplified : Cortex provides intuitive APIs for defining sources, sinks, and operators, enabling seamless pipeline creation with minimal boilerplate code.
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Rich State Management : Includes out-of-the-box support for in-memory and persistent state stores (e.g., RocksDB) to handle stateful computations like aggregations and windowing.
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Built-in Operators : Offers a variety of prebuilt operators, including:
- Transformation (Map)
- Filtering (Filter)
- Aggregations (GroupBy, Aggregate)
- Windowing (Tumbling, Sliding, Session Windows)
- Extensible and Customizable
Developers can easily create custom operators, state stores, or telemetry integrations tailored to specific needs.
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Telemetry and Monitoring Integrates with industry-standard telemetry frameworks (e.g., OpenTelemetry) for real-time metrics, logging, and tracing.
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Error Resilience Built-in mechanisms for handling errors gracefully during pipeline execution.
Why Use Cortex?
Section titled “Why Use Cortex?”-
Developer Efficiency : Cortex’s abstraction layer reduces development complexity, allowing you to build and iterate faster on data-intensive applications.
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Scalability and Performance : With support for scalable state stores and efficient operator chaining, Cortex ensures high throughput and low latency, even under heavy data loads.
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Flexible Architecture : The framework can be integrated into existing systems or used to design entirely new data workflows, making it a versatile tool for a wide range of industries.
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Production Ready : Designed for real-world scenarios, Cortex handles concurrency, persistence, and fault tolerance with ease, making it ready for deployment in mission-critical environments.
flowchart LR
A([IDataStore]) -->|Implements| A1(InMemoryStateStore)
A([IDataStore]) -->|Implements| A2(CassandraStateStore)
A([IDataStore]) -->|Implements| A3(ClickHouseStateStore)
A([IDataStore]) -->|Implements| A4(MongoDbStateStore)
A([IDataStore]) -->|Implements| A5(SqlServerStateStore)
A([IDataStore]) -->|Implements| A6(PostgresStateStore)
A([IDataStore]) -->|Implements| A7(RocksDbStateStore)
A([IDataStore]) -->|Implements| A8(SqliteKeyValueStateStore)
subgraph DataStores
A1(InMemoryStateStore)
A2(CassandraStateStore)
A3(ClickHouseStateStore)
A4(MongoDbStateStore)
A5(SqlServerStateStore)
A6(PostgresStateStore)
A7(RocksDbStateStore)
A8(SqliteKeyValueStateStore)
end
B([ITable]) -->|Uses| A([IDataStore])
B([ITable]) --> A9(Table)
subgraph StateLayer
A([IDataStore])
B([ITable])
A9(Table)
end
subgraph OperatorLayer
C(IStatefulOperator) -->|Holds references to| A([IDataStore])
C(IStatefulOperator) --> D(Stateful logic, e.g. AggregateOperator, GroupByKeyOperator, etc.)
end
S(Your Application/Stream) --> C(IStatefulOperator)
style A stroke:#333,stroke-width:2px,stroke-dasharray: 5 5
style B stroke:#333,stroke-width:2px,stroke-dasharray: 5 5
style C stroke:#333,stroke-width:2px,stroke-dasharray: 5 5
Core Use Cases
Section titled “Core Use Cases”- Real-Time Analytics: Build pipelines to analyze data streams, such as user activity logs or IoT sensor readings, in real-time.
- Event-Driven Systems: Process events dynamically, triggering actions based on business rules or aggregated data.
- Session Management: Manage stateful sessions for applications like chat systems or gaming platforms.
- Streaming Data Transformation: Transform incoming data streams into enriched formats for downstream systems.
How Cortex Fits in the Data Ecosystem
Section titled “How Cortex Fits in the Data Ecosystem”Cortex seamlessly integrates with your existing architecture:
- Data Sources: Connects to a variety of data sources, including message brokers like Kafka or custom source operators.
- State Management: Supports persistence using RocksDB or in-memory state stores for low-latency operations.
- Monitoring Tools: Works with telemetry systems to provide deep insights into pipeline health and performance.
Whether you’re an engineer looking to simplify complex stream processing workflows or a data scientist aiming to operationalize data models, Cortex provides the building blocks for success.