InfoKalashE-Commerce
Curabitur auctor quam ut iaculis suscipit. Morbi ullamcorper tellus eu purus dictum convallis. Duis posuere dui sit amet pellentesque malesuada. Morbi ultrices tortor ut diam molestie, vel pharetra lectus lacinia. Lorem ipsum dolor sit amet.
Sports
Etiam vehicula commodo nunc, ut tincidunt risus aliquam sit amet. Vivamus ut velit ut odio malesuada tincidunt ut non eros. Curabitur vel quam varius, ullamcorper mi quis, ultrices eros. Nam eget mi ut diam elementum facilisis vehicula eget augue.
Construction
Lorem ipsum dolor sit amet, consectetur adipiscing elit. Donec luctus, nunc in iaculis vestibulum, nunc ex convallis est, ut viverra velit sapien ac erat. Vivamus aliquet mi tellus, vel viverra ex blandit sed. Sed blandit lobortis risus. Aliquam blandit cursus ex sed iaculis.
Medicine
In vel nulla ac enim pellentesque tristique vel non dui. Integer vulputate ex leo, in accumsan purus consectetur quis. Cras scelerisque orci vel dapibus volutpat. In et consectetur enim. Maecenas lobortis viverra tortor, quis fermentum sem volutpat sit amet.
Real Estate
Donec consequat nibh at urna tincidunt tempor. Integer quis lobortis felis. Nulla id quam vestibulum, aliquam mauris vitae, auctor ex. Aliquam augue nulla, faucibus sed lacus ac, placerat elementum nisi. Curabitur enim nunc, dictum et accumsan.
Wellness
Morbi ullamcorper tellus eu purus dictum convallis. Duis posuere dui sit amet pellentesque malesuada. Morbi ultrices tortor ut diam molestie, vel pharetra lectus lacinia. Lorem ipsum dolor sit amet, consectetur adipiscing elit. Aenean varius lectus lectus.
Now we have different technologies which helps to ingest data in a faster way depending our needs. We @InfoKalash have experience in ingesting data in many different ways. Data Ingestion in different ways can be percieive in 2 main categories - ETL as a traditional way
- Data Ingestion via Distributed way, but using persistant memory ( Apache Kafka)
- Data Ingestion via Distributed way, but using In memory ( Apaceh Spark )
All 3 above are the valid Data Ingestion patterns for different data peipleine needs. Few lines on the different needs-
1. ETL way - Traditional ETL teams managing bulk data.
2. Distributed Persistant way - For more reliable data transfer, for resiliance, this is a preferred way.
3. Distributed InMemory way - For systems deriving insights ( ML based), for systems which are non transactional in nature.
