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Top 8 Data Warehouse Tools

SnowflakeOracle ExadataVerticaTeradataOracle Database ApplianceSAP BW4HANAApache HadoopIBM Netezza Performance Server
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    It was relatively easy to use, and it was easy for people to convert to it. I like the fact that we don't need a DBA. It automatically scales stuff.
  2. leader badge
    Exadata is a fantastic machine. Two features stand out. The first is the resource input/output management tool that allows you to manage the resources to the neck on the Exadata box.
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  4. It's the fastest database I have ever tested. That's the most important feature of Vertica. Vertica has a few features that I like. From an architecture standpoint, they have separated compute and storage. So you have low-cost object storage for primary storage and the ability to have several sub-clusters working off the same ObjectStore. So it provides workload isolation.
  5. Teradata features high productivity and reliability because it has several redundancy options, so the system is always up and running. Teradata has good performance, the response times are very fast. Overall the solution is easy to use. When we do the transformation, we have all of our staging and aggregation data available.
  6. If the database goes down on one of the servers, the load is automatically shifted to another server. You can troubleshoot the one that is down without affecting uptime.
  7. The most valuable feature is that we can transform a huge amount of data and apply business logic as per the requirements.I like that it's quite quick.
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  9. Hadoop is extensible — it's elastic. Hadoop is designed to be scalable, so I don't think that it has limitations in regards to scalability.
  10. The performance is most important to me, and it helps our ability to make business decisions quickly.We are able to execute very complex queries. Over 90 percent of our query executions are one second or less. We do millions of queries everyday.
How does a data warehouse work?

A data warehouse serves as a central repository for information that flows into it from various databases. The data is then processed, standardized, and merged so that it can be accessed by users in spreadsheets, SQL clients, and business intelligence tools. Once all of the data is compiled in one place, organization executives can analyze it and mine the data for patterns that will assist in making business decisions.

What is data warehousing used for?

Data warehousing is used in many sectors, including:

  • Airline industry - for operations purposes such as crew assignments, route profitability analysis, and frequent flyer programs.
  • Banking - for managing resources, performance analysis, and market research.
  • Healthcare - for generating patient treatment reports, strategizing and predicting outcomes, and sharing data with insurance companies and medical aid services.
  • Hospitality industry - for designing and estimating advertising campaigns and promotions based on client travel patterns and feedback.
  • Investment and insurance sector - for analyzing customer trends and tracking market movements.
  • Public sector - for gathering of intelligence such as tax records and health policy records.
  • Retail chains - for distribution and marketing, for tracking customer buying patterns and for determining prices.
  • Telecommunications - for making sales and distribution decisions.
What is the Difference Between a Data Warehouse and a Database?

Data warehouses and databases are both used for storing data. A database is used to store a large amount of real-time information, such as which items are in stock or have been sold. It processes your company’s daily transactions via simple queries. A data warehouse (DW or DWH) compiles historical (not current) data from multiple sources within your organization, handling complex queries which are used to create and analyze reports and then extract insights and make business decisions.


Databases and data warehouses process data differently. Databases use OLTP (online transactional processing) to quickly update a large amount of simple online transactions. OLTP responds immediately and therefore is useful in processing real-time data. Data warehouses, on the other hand, use OLAP (online analytical processing) to analyze large amounts of data and find out trends from them, such as how much is sold each day.

Types of Data Warehouse

There are three main kinds of data warehouse:

1. Enterprise Data Warehouse (EDW). This is a centralized warehouse that offers a unified approach for representing and organizing data. It allows data to be classified according to subject and helps executives to make tactical and strategic decisions.

2. Operational Data Store (ODS). This database integrates data from various sources for operational reporting and decision-making, and complements the EDW.

3. Data Mart. This subset of the data warehouse is specially designed for use by a specific department within the business, such as sales or finance, and can collect data directly from the sources.

Benefits of a Data Warehouse

The benefits of a data warehouse include:

  1. Enhances the quality and consistency of data. Data in a data warehouse is converted into a consistent format. With data across the organization standardized, the data will be more accurate, which means decisions made based on it will be more solid.
  2. Saves time and money. A data warehouse preserves, standardizes, and stores data from various sources, which aids in consolidating and integrating the data. Company executives can also query the data in the data warehouse themselves without IT support, which saves time as well as money.
  3. Delivers enhanced business intelligence from multiple sources. In addition, data warehouses can be easily applied to all of your business’s processes, such as sales, market segmentation, inventory, and financial management.
  4. Assists with decision-making and forecasting, including identifying potential KPIs and gauging predicted results.
  5. Streamlines the information flow to all parties.
  6. Provides a competitive advantage by offering a holistic view of the company’s standing and allowing executives to evaluate risks and opportunities.
  7. Generates a high ROI (return on investment).


Find out what your peers are saying about Snowflake Computing, Oracle, Micro Focus and others in Data Warehouse. Updated: January 2022.
564,143 professionals have used our research since 2012.