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24FebFebruary 24, 2025

The Role of Materialized Views in Modern Data Stream Processing Architectures + RisingWave

Incremental computation in data streaming means updating results as fresh data comes in, without redoing all calculations from the beginning. This method is essential for handling ever-changing information, like real-time sensor readings social media streams, or stock market figures. In a traditional, non-entrepreneurial calculation model, we need to process the entire dataset every time we get a new piece of data. It can be incompetent and slow. In incremental calculations, only the part of the result affected by new...

By Gautam GoswamiBig Data, Data Analysis, Data Engineering, Data Science, Processing Engine, Storage MechanismBig Data, Data Streaming, datainmotion, risingwave, streaming dataComments Off

23JanJanuary 23, 2024

Integrating rate-limiting and backpressure strategies synergistically to handle and alleviate consumer lag in Apache Kafka

Apache Kafka stands as a robust distributed streaming platform. However, like any system, it is imperative to proficiently oversee and control latency for optimal performance. Kafka Consumer Lag refers to the variance between the most recent message within a Kafka topic and the message that has been processed by a consumer. This lag may arise when the consumer struggles to match the pace at which new messages are generated and appended to the topic. Consumer lag in Kafka may...

By Gautam GoswamiApache Kafka, Big Data, Data EngineeringApache Kafka, Data Streaming, kafka consumerComments Off

25AugAugust 25, 2022

Importance of Schema Registry on Kafka Based Data Streaming Pipelines

Needless to say Apache Kafka delivers messages to both real-time and batch consumers without performance degradation and in addition to that gaining enormous momentum as a foremost component for data streaming pipelines too. Credit card fraud detection, predictive maintenance, or real-time analytics, building streaming IoT platform, etc are the example of real-time use cases. To handle massive amounts of data ingestion, Apache Kafka is the cornerstone of a robust IoT data platform. A schema defines the structure of the data...

By Gautam GoswamiApache Kafka, Architecture, Data Engineering, Data IngestionApache Kafka, assign schema info in the schema registry, Avro, building streaming IoT platform, centralized schema management, Confluent Schema Registry, Credit card fraud detection, Data ingestion, data pipeline, Data Pipelines, Data Streaming, deserialized the messages, distributed storage layer for schemas, Hadoop, JSON Schema, Kafka based data pipeline, Kafka based data streaming pipelines, Kafka connect, Kafka producers and consumers, multi-broker Kafka topic, Multi-node kafka cluster, predictive maintenance, producer-consumer contract, Protobuf schemas, real-time analytics, schema change history, schema evolution, schema of registered data streams, schema registry, Schema Registry on Kafka Based Data Streaming Pipelines, Schema Registry on Kafka Streaming Pipelines, service layer for metadata, streaming applications, streaming data to Kafka topicComments Off

30NovNovember 30, 2017

Basic Understanding Of Stateful Data Streaming Supported By Apache Flink

Technologies related to Big Data processing platform are enhancing the maturity in order to efficiently execute the streaming data which is becoming a major focus point to take business decision instantly specially in telecom and retail sector. Collecting data continuously from the various sensors installed/fitted with an industrial heavy equipment, click stream on an e-commerce application’s navigation etc can be considered as streaming data generation sources. By leveraging streaming application, we can process/analyze these continues flow of data without...

By Kislay KomalData Engineering, Processing EngineApache Flink, Big Data processing platform, checkpoint, concurrent updates, Data Streaming, Flink, HDFS, KeyBy, maintain parallelism, protecting streaming application from failure, savepoint., Stateful Data Streaming, Stateful Data Streaming Supported By Apache Flink, stateful operation, Stateless computation, Statelful computation, streaming application, Understanding Of Stateful Data Streaming Supported By Apache FlinkComments Off

Tag - Data Streaming

The Role of Materialized Views in Modern Data Stream Processing Architectures + RisingWave

Integrating rate-limiting and backpressure strategies synergistically to handle and alleviate consumer lag in Apache Kafka

Importance of Schema Registry on Kafka Based Data Streaming Pipelines

Basic Understanding Of Stateful Data Streaming Supported By Apache Flink

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