Kafka Streams
Apache Kafka: A Distributed Streaming Platform.
Some of the top features or benefits of Kafka Streams are: Scalability, Integration with Kafka, Exactly-once semantics, Microservices Architecture, Stateful and Stateless Processing, and Fault Tolerant. You can visit the info page to learn more.
Kafka Streams Alternatives & Competitors
The best Kafka Streams alternatives based on verified products, community votes, reviews and other factors.
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Open-Source Alternatives.
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Flink is a streaming dataflow engine that provides data distribution, communication, and fault tolerance for distributed computations.
Key Apache Flink features:
Real-time Stream Processing Event Time Processing State Management Fault Tolerance
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Apache Kafka is an open-source message broker project developed by the Apache Software Foundation written in Scala.
Key Apache Kafka features:
High Throughput Scalability Fault Tolerance Durability
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Making Today: Stay Organized, Work Faster.
Key Making Today features:
Dashboard Multiple dashboards Popular integrations Multiple Platform support
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Apache Storm is a free and open source distributed realtime computation system.
Key Apache Storm features:
Real-Time Processing Scalability Fault Tolerance Broad Language Support
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Apache Spark is an engine for big data processing, with built-in modules for streaming, SQL, machine learning and graph processing.
Key Apache Spark features:
Speed Ease of Use Advanced Analytics Scalability
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Confluent offers a real-time data platform built around Apache Kafka.
Key Confluent features:
Scalability Real-Time Data Processing Comprehensive Ecosystem Ease of Use
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Confluent KSQL is the streaming SQL engine that enables real-time data processing against Apache Kafka®.
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An easy to use, powerful, and reliable system to process and distribute data.
Key Apache NiFi features:
User-Friendly Interface Extensive Connector Support Real-time Data Processing Scalability
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RisingWave is a stream processing platform that utilizes SQL to enhance data analysis, offering improved insights on real-time data.
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Airflow is a platform to programmaticaly author, schedule and monitor data pipelines.
Key Apache Airflow features:
Scalability Extensibility Visualization Flexibility
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A Streaming Database for Real-Time Applications.
Key Materialize features:
Real-time Analytics SQL Support Consistency Integration with Kafka
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A fully managed data warehouse for large-scale data analytics.
Key Google BigQuery features:
Scalability Speed Integrations Automatic Optimization
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Apache Beam provides an advanced unified programming model to implement batch and streaming data processing jobs.
Key Apache Beam features:
Unified Model Portability Rich SDKs Windowing and Triggering
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An innovative streaming SQL database and real-time analytics platform. Fast, powerful and intuitive.
Key Timeplus features:
Unified streaming and historical data process Tumble, hopping, session window Materialized views Realtime charts, dashboards, alerts
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