Remove Aggregated Data Remove Events Remove Metadata Remove Relational Database
article thumbnail

AWS Glue-Unleashing the Power of Serverless ETL Effortlessly

ProjectPro

Application programming interfaces (APIs) are used to modify the retrieved data set for integration and to support users in keeping track of all the jobs. Users can schedule ETL jobs, and they can also choose the events that will trigger them. Then, Glue writes the job's metadata into the embedded AWS Glue Data Catalog.

AWS 98
article thumbnail

ELT Process: Key Components, Benefits, and Tools to Build ELT Pipelines

AltexSoft

All available data is pulled from a particular data source. This process can involve extracting all rows and columns of data from a relational database, all records from a file, or all data from an API endpoint. Partial data extraction with update notifications. Aggregation. Full extraction.

Process 52
Insiders

Sign Up for our Newsletter

This site is protected by reCAPTCHA and the Google Privacy Policy and Terms of Service apply.

article thumbnail

Sqoop vs. Flume Battle of the Hadoop ETL tools

ProjectPro

The major difference between Sqoop and Flume is that Sqoop is used for loading data from relational databases into HDFS while Flume is used to capture a stream of moving data. Table of Contents Hadoop ETL tools: Sqoop vs Flume-Comparison of the two Best Data Ingestion Tools What is Sqoop in Hadoop?

article thumbnail

20 Best Open Source Big Data Projects to Contribute on GitHub

ProjectPro

It serves as a distributed processing engine for both categories of data streams: unbounded and bounded. Support for stream and batch processing, comprehensive state management, event-time processing semantics, and consistency guarantee for the state are just a few of Flink's capabilities. However, Trino is not limited to HDFS access.

article thumbnail

The Good and the Bad of the Elasticsearch Search and Analytics Engine

AltexSoft

Analysis of logs, metrics, and security events. With Elasticsearch, you can aggregate and analyze large streams of logs, metrics, and security events in near real-time, making it indispensable for system monitoring and security information and event management (SIEM). Real-time behavior modeling with ML.

article thumbnail

The Modern Data Stack: What It Is, How It Works, Use Cases, and Ways to Implement

AltexSoft

Moreover, over 20 percent of surveyed companies were found to be utilizing 1,000 or more data sources to provide data to analytics systems. These sources commonly include databases, SaaS products, and event streams. Databases store key information that powers a company’s product, such as user data and product data.

IT 59