This section mentions some of the popular tools to help you achieve a more efficient and practical data warehouse integration.
Amazon Redshift
Amazon Redshift is a cloud-based data warehouse for companies. As a fully-managed platform, Redshift processes petabytes of data in a matter of seconds. Among other perks, Redshift is also apt for automatic concurrency scaling. Through this automation, you can manipulate the data querying process and make it suitable for large-volume demands. Additionally, Redshift also helps companies scale data clusters and alternate between node types, thus optimizing the data warehouse performance and reducing the overall process costs.
If you care about full-speed data integration and analysis, then Redshift is a perfect data integration tool for you.
Microsoft Azure SQL Data Warehouse
Also, a cloud-based tool, Azure SQL Data Warehouse, is a handy Microsoft product. The tool helps companies maximize their efficiency in integrating and scaling petabyte volumes of data, both in loading and processing it. It also enables real-time reporting and uses a node system while enforcing MPP (Massively Parallel Processing).
The tool is perfect for optimizing queries intended for simultaneous processing, thus accelerating the extraction and visualizing of all business insights.
Google BigQuery
BigQuery is yet another efficient data warehousing tool. It can also be easily integrated with other Google cloud services such as CloudML and TensorFlow to build powerful AI and machine learning models.
BigQuery also manages petabyte-scale data queries in seconds and provides you with real-time analysis. As a cloud-based tool, BigQuery can be used to perform geospatial analytics to assess location-based data. The tool also separates data storage and computing, thus scaling the data processing and using memory sources based on your business needs.
Snowflake
Snowflake is a really practical data warehouse integration tool, as it allows you to set up an enterprise-level cloud data warehouse. With Snowflake, you can analyze data stemming from several sources, both structured and unstructured.
Snowflake’s architecture is cluster-oriented and separates the processing power of a data warehouse from data storage. Based on your users’ activity, you can easily scale CPU resources and optimize your query performance. The result? You can obtain fast, accurate insights from your data at a reasonable cost.
Teradata
Teradata is a data warehouse integration platform that does more than one job. It allows you to collect massive volumes of enterprise data in the cloud. Also, it supports speedy parallel querying and analyses of this data.
Teradata also comes with a smart in-memory processing option, which maximizes the database's performance at no additional cost.