MongoDB Atlas Data Lake
AWS S3 and MongoDB Atlas Data Lake is a comprehensive in-place query and analysis function that offers a managed service to meet the needs of data analysis. It supports several formats of data such as – JSON, BSON, CSV and Parquet format of data. MongoDB Atlas Data Lake uses MongoDB languages and is easily compatible with several MongoDB products and services. This means that organizations can gain deep insights from their data by carrying out analytical activities on them without having to migrate or modify them.
Use Case:
A common application can be seen in the big data implementation of MongoDB Atlas Data Lake. Amazon S3 provides scalable, secure object storage and AWS users can harness MongoDB Atlas Data Lake to query this data natively with MongoDB query and aggregation frameworks.
Case Study:
One of the organizations using media streaming services opted for MongoDB Atlas Data Lake for viewing user behaviour as well as the content consumption pattern from relevant data. They used the Amazon S3 technology system where they had a huge pile of unstructured and semi-structured data which included user activity logs, viewing histories, and many more content metadata. They could perform calculations on this data without having to transfer it to a separate analytics platform using MongoDB Atlas Data Lake. This enabled them to understand what users might be interested in, learn about content that it was plural or singular more favourited, and enhance the recommendation methods. They were also able to augment it with further context from their MongoDB databases in MongoDB Atlas to obtain a more holistic picture of what was happening at their companies.
Top Data Ingestion Tools for 2024
To capture data for utilising the informational value in today’s environment, the ingestion of data is of high importance to organisations. Data ingestion tools are especially helpful in this process and are responsible for transferring data from origin to storage and/or processing environments. As enterprises deliver more diverse data, the importance of the right ingestion tools becomes even more pronounced.
This guide focuses on the top data ingestion tools 2024 detailing the features, components, and fit for organization applications to help organizations make the right choice for their data architecture plan.
Table of Content
- Apache NiFi
- Apache Kafka
- AWS Glue
- Google Cloud Dataflow
- Microsoft Azure Data Factory
- StreamSets Data Collector
- Talend Data Integration
- Informatica Intelligent Cloud Services
- Matillion ETL
- Snowflake Data Cloud
- MongoDB Atlas Data Lake
- Talend Data Integration
- Azure Synapse Analytics
- IBM DataStage
- Alteryx