Real Time
23 items tagged with "real-time"
Tutorials1
Blueprints3
Batch to Streaming Blueprint
Migration blueprint for converting batch processing to real-time streaming
Batch ML Scoring to Real-Time Model Serving Blueprint
Move from nightly batch ML scoring to low-latency online model serving with a model server, feature lookups, and autoscaling.
REST Polling to GraphQL Subscriptions Blueprint
Replace client REST polling for fresh data with real-time GraphQL subscriptions over WebSockets for push updates and lower load.
Products3
Reference Architectures1
Stacks12
Phoenix LiveView
An Elixir stack using Phoenix LiveView to build real-time, server-rendered interactive UIs over WebSockets with little JavaScript.
Phoenix Elixir Stack
Concurrent Elixir backend using the Phoenix framework on the BEAM VM with PostgreSQL for fault-tolerant, real-time, highly concurrent services.
Kafka + Flink Streaming Stack
Real-time stream processing stack pairing Apache Kafka for durable event streams with Apache Flink for stateful, low-latency computation.
Feast Feature Store Stack
Feature store pattern using Feast to define, materialize, and serve consistent ML features from an offline warehouse and a low-latency online store.
ClickHouse Real-Time Analytics Stack
High-performance analytics stack: ClickHouse ingests event streams from Kafka and serves sub-second OLAP queries powering user-facing dashboards.
Kafka + ksqlDB
A stream-processing stack using Apache Kafka for event transport and ksqlDB for SQL-based streaming transformations and materialized views.
Flink + Apache Paimon
A streaming lakehouse stack using Apache Flink for unified stream and batch processing over Apache Paimon's high-update table format.
ClickHouse + Grafana
A real-time analytics stack using ClickHouse as a fast columnar OLAP database with Grafana for dashboards over high-volume event data.
Apache Druid + Superset
A real-time OLAP stack using Apache Druid for sub-second slice-and-dice queries and Apache Superset for self-service exploration.
Apache Pinot Real-Time Analytics
A user-facing analytics stack built on Apache Pinot for ultra-low-latency, high-throughput queries over fresh streaming data.
Tecton Feature Store
A production feature platform stack using Tecton to define, compute, and serve consistent ML features for training and real-time inference.
Kafka + Flink Streaming Lakehouse
An end-to-end streaming lakehouse stack: Kafka ingests events, Flink processes them in real time, and Iceberg tables on S3 serve analytics.
Glossaries2
WebSocket
WebSocket is a protocol that provides a persistent, full-duplex communication channel over a single TCP connection, enabling real-time two-way data exchange between client and server.
Server-Sent Events
Server-Sent Events (SSE) is a web standard that lets a server push a continuous, one-way stream of text updates to a client over a single long-lived HTTP connection.