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02AugAugust 2, 2023

How Kafka Works?

#realtimedata streaming with #kafka is a popular and powerful approach to handle large volumes of data and facilitate communication between different systems and applications. #apachekafka is an open-source distributed event streaming platform that allows you to publish, subscribe, store, and process streams of records. Here's a general overview of how real-time data streaming with Kafka works: Topic and Message Model: Data is organized into topics, which are essentially log-like data streams. Each message within a topic consists of a key, value, and timestamp. Publishers...

By Kislay KomalApache Kafka, Data EngineeringApache Kafka, How kafka works?, Kafka, kafka. working with apache kafkaComments Off

05SepSeptember 5, 2022

Orchestrating Multi-Brokers Kafka Cluster through CLI Commands

This short article aims to highlight the list of commands to manage a running multi-broker multi-topic Kafka cluster utilizing built-in scripts. These commands will be helpful/beneficial when the cluster is not integrated or hooked up with any third party administrative tool having GUI facilities to administer or control on the fly. Of course, most of them are not free to use. Can refer here to set up a multi-broker Kafka cluster.By executing the built-in scripts available inside the bin...

By Gautam GoswamiApache Kafka, Data EngineeringApache Kafka, Big Data, bin directory of the Kafka, Kafka, Kafka Administration, list of commands to run multi-broker multi-topic Kafka cluster, modify a Kafka topic, number of replication factor can’t be higher than the number of broker in the cluster, Orchestrating Multi-Brokers Kafka Cluster, Orchestrating Multi-Brokers Kafka Cluster through CLI Commands, retention time of a Kafka topic, retrieve log directories information from the kafka brokersComments Off

18AugAugust 18, 2022

Why Kappa Architecture for processing of streaming data. Have competence to superseding Lambda Architecture?

Data is quickly becoming the new currency of the digital economy, but it is useless if it can’t be processed. The processing of data is essential for subsequent decision-making or executable actions either by the human brain or various devices/applications etc. There are two primary ways of processing data namely batch processing and stream processing. Typically batch processing has been adopted for very large data sets and projects where there is a necessity for deeper data analysis, on the...

By Gautam GoswamiArchitecture, Data Engineering, Data IngestionAmazon Kinesis, Apache Flink, Apache Hadoop, Apache Kafka, Apache Samza, Apache Storm, batch processing layer, Big Data, Data Lake, data warehouse, event based Kappa architecture, event streaming platform, Hadoop Data Lake, HDFS, Kafka, Kafka Architecture Development Kafka Architecture Development, Kappa Architecture, Kappa Architecture for streaming data, Lambda Architecture, Map-Reduce framework, messaging engine, multiple stream processors, stream processing application, streaming computation system, streaming data analyticsComments Off

11JanJanuary 11, 2021

Data Absorption (Ingestion)

By Kislay KomalAbsorption, accumulate business data, Apache Flume, Apache Kafka, Apache Sqoop, Big Data Analysis service in Bangalore, Big data ingestion architecture, central data repository, creating hadoop data lake, Data Absorption, Data Absorption Service in Bangalore, data analytics, Data ingestion, data ingestion architecture, Data Ingestion Service in Bangalore, Data Lake, data pipeline, distributed centralized repository, Hadoop Data Lake, Hadoop Data Lake Creation, heterogeneous data, how to create hadoop data lake, IDropper, Ingestion, ingestion architecture, Kafka, moving heterogeneous data, poc, preserve business data, production server log files, proof of concept, rdbms, Sqoop, structured data, unstructured data, using apache flumeComments Off

29AugAugust 29, 2017

Data Ingestion phase for migrating enterprise data into Hadoop Data Lake

The Big Data solutions helps to achieve valuable information to iron out the accurate strategic business decision. Exponential growth of digitalization, social media, telecommunication etc. are fueling enormous data generation everywhere. Prior to process of huge volume of data, we should have efficient data storage mechanism in a distributed manner to hold any form of data starting from structured to unstructured. Hadoop distributed file systems (HDFS) can be leveraged efficiently as data lake by installing on multi node cluster....

By Gautam GoswamiData Engineering, Data IngestionApache software foundation, Apache Sqoop, ata storage mechanism, ATG database, ATG database schema, cloud service providers, collecting Twitter streaming data, Couchbase, Data ingestion, Data Ingestion phase for migrating enterprise data into Hadoop Data Lake, Data Lake, data storage mechanism, DB2, Digitization, distributed storage, efficient data storage mechanism, ELT, enterprise data, export data from Kafka topic to HDFS, fault-tolerant, Flume, Hadoop, HADOOP Cluster, Hadoop Data Lake, Hadoop distributed file systems, Hadoop multi node cluster, HDFS, Hive, huge data reservoirs, huge volume of data, Ingestion, JDBC connector, JDBC protocol, Kafka, Kafka HDFS connector, Kafka to HDFS, Mainframe, mainframe dataset to HDFS, MapReduce, MapReduce distributed computing, migrating enterprise data, moving large amount of streaming data into HDFS, multi node cluster, multiple delimited text files, MySQL, Netezza, NoSql DB, NoSql Stores, Oracle, Oracle 11g Enterprise Edition, Oracle ATG Platform, parallel import process, parallel processing, pluggable mechanism, PostgreSQL, read the messages from Kafka topic, SQLServer, Sqoop, Sqoop installation, Strom, Using Kafka HDFS connectorComments Off

21AprApril 21, 2017

Irisidea’s Competencies

The technical leadership team is the core strength of Irisidea Technologies. Irisidea's business and technical experts not only work closely with clients to provide cost effective, robust solutions to their business needs, but also dedicate a part of their time regularly in research work and keeping themselves on the edge of technology. Each individual of this team is not only an expert in his domain, but he also strives to expand his knowledge horizon by learning new technologies that...

By Kislay Komal.NET Framework 3.5/4.0, 2008, Ability to quickly learn and get expertise on new domains & technologies, Ability to Work in Harmony with Co-Workers, ADO.NET, AI Application Maintenance, AI Deployment, AI Deployment Environment Setup, AI Development Environment Setup, AI Implementation, AI Support, AI Testing, AJAX, Ambari, Apache Ranger, Application Platforms/Tools, Artificial Intelligence, ASP.NET, ATG Commerce Designing Tools, C#.NET, CMS Tools, Css, Curl, Databases, Deep learning, Demandware, Determination and Persistence, Development and Maintenance, Development Platforms, Development Tools, DHTML, DOM, Dreamweaver CS4, Drupal E-Commerce Platforms, Eclipse, endeca, Enthusiastic & passionate team, Flash CS4, Flexibility to adjust as per the situations project demand, Flume, Frameworks, Hadoop and its ecosystem, Hibernate, Hive, HTML, IBM DB/2, Illustrator Data Bases, j2ee, Java Expertise, Java Scripts, JavaScript, JBoss Java Technologies : Java, Joomla, JProbe, JProfiler, JQuery, JSP, Kafka, Languages, Linux, machine learning, magento, Microsoft Office SharePoint Server (MOSS) 2007, Microsoft SQL Server, Microsoft Technologies Expertise, MS Exchange, MS Office, MS SQL Server 2005/2008, MS-SQL Server, Multi Nodes Hadoop Cluster Management, MySQL, MySQL Profiler, NET, Net Beans, Nifi, OfBiz, Oracle, Oracle Cloud Commerce, Oracle Commerce, Oracle Development Platforms, Oracle-ATG, Photoshop CS4, PHP, Predictive Analytics, ROR, SalesForce Commerce Cloud, SharePoint 2010, SOAP, Social Data Analytics, Spring, Sqoop, Strong communication skills, Struts, Tomcat, Visual Studio 2008/2010, Web Services, Web/Application Servers, website design, Windows, Windows Server 2003, WordPress, WSS 3.0, XHTML, XML, Zen cart, ZookeeperComments Off

Tag - Kafka

How Kafka Works?

Why Kappa Architecture for processing of streaming data. Have competence to superseding Lambda Architecture?

Data Absorption (Ingestion)

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