Analytics Database

What is an analytics database? It is a sort of database specifically built to store and handle massive amounts of data in order to do data analytics and reporting. It is designed to help corporate intelligence and decision-making processes by allowing for complicated searches, data aggregation, and speedy information retrieval. It is specifically designed to support business intelligence (BI) and analytic applications, typically as part of a data warehouse or data mart.

Why to use Analytics Database? 

We’re now living in an age where data, and more importantly predictive analytics and insights from data, are vital for the success of any business. The right analytical database allows to ask those all-important ‘why?’ questions and push the boundaries of what’s possible with your data by allowing you to unearth useful insights and information from your data volumes.

Transactional-based databases are for day-to-day operations, analytic databases support blue-sky, “what if?” thinking and allow you to unearth insights and information from your data volumes.

What are Key Characteristics of an Analytics Database?

  • Columnar Storage: Data is stored in columns rather than rows, allowing for better compression and query efficiency.
  • Parallel Processing: Analytics databases frequently utilize parallel processing to divide query workloads over numerous servers or nodes, resulting in speedier data retrieval.
  • Aggregation and Transformation: They provide functions for aggregating, filtering, and manipulating data in order to extract insights and create reports.
  • Scalability: Analytics databases may be expanded horizontally by adding more nodes or servers to manage higher data volumes and increasing workloads.
  • Integration: They frequently collaborate with data visualization tools, business intelligence platforms, and data processing frameworks to improve data analysis and reporting.
  • Performance Optimization: To guarantee quick query execution, many optimization techniques are used, including indexing, caching, and query optimization.
  • Data Warehousing: Analytics databases are often used in data warehousing solutions to store historical data for analysis.
  • SQL Support: They usually support SQL (Structured Query Language), which makes it easier for analysts and data scientists to deal with data.

How Exasol Uses an Analytics Database?

EXASOL is the world’s fastest analytics database according to the TPC-H benchmark for analytic scenarios.

Latest Analytics Database Insights

Exasol’s fast in-memory database set a performance record in the TPC-H benchmark for clustered, decision support databases, and extended these performance and price/performance records over the years.

Read more on the fastest in-memory database >

It’s time to kiss goodbye to slow queries and say hello to super-fast answers. However, some factors need to be considered to choose the optimal one for your business.

Read the 5 things to consider >

Analytic databases are considered to be a sound solution for delivering the right information for making economic decisions and securing the business’ market position. The optimal architecture for a company depends greatly on the task at hand.

Read the checklist >

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