infinyon/fluvio

Features

• Streaming Data Processing - Provides a distributed engine for analyzing and transforming continuous streams of data in real time.
• Event-Driven Data Pipelines - Builds event-driven pipelines that integrate streaming with stateful processing to transform data in motion.
• Real-Time Data Streaming - Provides a high-performance platform for collecting, persisting, and replicating real-time event streams.
• Stream Processing Runtimes - Executes custom business logic via WebAssembly modules to transform and filter data streams in motion without cluster restarts.
• Partitioned Data Replicators - Distributes data partition copies across nodes with automated leader election for continuous availability.
• Wasm Post-Processing - Uses WebAssembly modules to apply reusable processing functions and transformations to data streams.
• Topic Management - Provides the ability to define and organize named storage entities for distributing real-time data streams.
• Data Processing Pipelines - Supports the creation of hierarchical processing flows including stateful operations, data enrichment, and windowing.
• Real-Time Data Processors - Implements a framework for building stateful workflows that ingest, enrich, and export data.
• Multi-Source Data Integration - Integrates various external data sources directly into the streaming pipeline for ingestion.
• Data Transformation Functions - Applies user-defined functions to manipulate or filter data as it moves through connectors.
• Stream Transformation Logic - Allows the execution of custom business logic in various languages to transform data streams.
• Distributed Event Streaming Platforms - Ships a distributed system for high-throughput collection, persistence, and replication of real-time data streams.
• Data Partitioning - Distributes load and increases throughput by splitting individual topics into parallel data partitions.
• External Data Connectors - Provides a pluggable architecture of inbound and outbound connectors to ingest data from external protocols into streams.
• External Data Ingestion - Automatically pipes information from external services and endpoints into live streams via connectors.
• Horizontal Scaling - Supports horizontal scaling by adding declarative processing units and storage nodes to increase cluster capacity.
• Topic Offset Consumption - Enables reading a sequence of records from a stream starting at a specific offset.
• Log-Structured Storage - Uses a log-structured storage engine to save immutable, append-only message segments for high-performance writes.
• Connector-Based Ingestion - Uses connectors to automatically pull data from external protocols and services.
• Data Stream Management - Facilitates the structural management of append-only time series streams used for events and metrics.
• Event Streaming Databases - Implements a database that persists events as immutable streams and delivers them to subscribers in real time.
• Programmable Stream Processing - Integrates WebAssembly to run high-performance custom processing logic for real-time stream transformations.
• Stream Partitioning - Splits topics into parallel partitions to distribute traffic and increase total throughput.
• Stream Record Producers - Enables sending individual data entries into a stream for downstream processing or storage.
• Stream Transformations - Performs record-based operations and windowed aggregations to create materialized views from streaming data.
• Wasm Transformations - Applies custom WebAssembly logic and filters to reshape data in motion.
• Topic Data Distribution - Enables pushing data into a topic for distribution and reading it back for processing.
• External Service Integrations - Polls data from external endpoints using connectors to automatically populate specific stream topics.
• Cloud Native Infrastructure - Provides a horizontally scalable data architecture designed for cloud-native environments and edge devices.
• Horizontal Scaling Deployments - Implements horizontally scaling deployments for distributed processing units and storage nodes.
• Cluster Resource Management - Provides a dedicated control plane API to manage the lifecycle of topics, replicas, and processing units.
• Message Stream Consumer Groups - Reads records from a topic starting from the most recent entry or the beginning using a scalable architecture.
• Topic Producers - Provides writer abstractions for producing messages to topics with partition assignment and compression.
• Stream Topic Publishing - Supports sending records to a stream with configurable batching and compression to optimize throughput.
• In-Line Stream Processing - Injects compiled WebAssembly modules for high-performance in-line data transformations and payload detection.
• Wasm Stream Processors - Executes compiled WebAssembly modules to transform and filter data in motion.
• Storage Immutability - Implements architectural patterns for treating stored data as fixed once written using zero-copy IO.
• Composable Workflows - Provides modular systems for chaining functions and operators into reusable, independently tested dataflow packages.
• Stream State Accumulation - Implements stream state accumulation for window-based aggregates on real-time data streams.
• Streaming Data Transformations - Executes custom functions to process or modify data in motion during production or consumption.
• Stream Record Consumption - Provides capabilities to read records from a stream by starting from a specific offset or listening for arrivals.
• Client Libraries - Provides native language bindings to integrate streaming functions directly into application logic.
• Custom Connector Development - Provides a command line tool for generating, testing, and deploying custom input and output adapters.
• Data Destination Connectors - Ships configuration interfaces for establishing connections to external target storage systems and databases.
• Transformation Chains - Sequences multiple processing modules into a pipeline for multi-step data manipulations.
• Edge Data Processing - Executes data processing and transformation binaries on ARM64 and other IoT devices.
• Data Export Connectors - Pushes processed information to external databases, object storage, and search engines via outbound connectors.
• Stream Deduplication - Removes redundant records from real-time data streams to ensure only unique entries are processed.
• Disk IO Optimization - Implements zero-copy disk IO to persist immutable event records while minimizing memory copying overhead.
• Server-Side Data Transformations - Executes programmable functions on the client or server side to modify, filter, or reshape data streams.
• Sink Data Loading - Implements loading of processed data streams into various target storage systems and analytical databases.
• State Management Stores - Provides centralized systems for managing and persisting application state using typed schemas.
• Deployment Command Line Interfaces - Ships a terminal-based tool for provisioning workers to execute data processing logic.
• Pipeline Orchestration - Manages the execution flow and data lifecycle of complex multi-stage analytics pipelines via declarative APIs.
• Connector Deployment - Allows loading compiled data processing modules into a running streaming cluster for active use.
• Resource Coordination - Implements a dedicated control plane to coordinate the lifecycle of topics and replicas independently from the data path.
• Distributed Leader Election - Uses automated leader election to maintain high availability and coordinate writes across the distributed cluster.
• Streaming Cluster Orchestration - Provides the ability to initialize and start a distributed cluster to manage stream collection and processing.
• Edge Computing Runtimes - Can be deployed as a lightweight binary on diverse architectures including ARM64 IoT devices.
• External Service Connectivity - Interfaces with ingress and egress services through a pluggable library of data connectors.
• Dataflow Visualizers - Provides graphical representations of dataflow hierarchies and runtime analytics.
• Cluster Health Monitoring - Provides interfaces for querying the health and status of stream partitions and replication.
• Runtime State Inspection - Allows inspection of real-time metrics and internal state of active dataflows.
• Data Pipelines - Programmable data streaming platform with in-line computation.

Istoric stele