Webinar: Using Data Indexes to Boost Performance and Minimize Footprint in Embedded Software
Are you using data indexes to boost performance in locating data objects in embedded software? If so, the right index can enhance lookup speed logarithmically, while reducing RAM and CPU demands. While the B-Tree is the best known index, there are many others can be more efficient in specific circumstances, such as ingeospatial/mapping and telecom/networking applications. This Webinar examines less well-known indexes including T-Tree, Hash table, R-Tree, Patricia trie and others. It emphasizes index implementation methods that avoid data duplication, to minimize memory footprint.
eXtremeDB provides a number of specialized indexes to facilitate particular types of database search and navigation.
- Patricia Trie (ideal for managing IP addresses)
- R-Tree (example using spatial coordinates)
- KD-Tree (example using Query-by-example)
- Trigram (using Trigram indexes for text searches)
- Autoid indexes and unique Object Id searches
- List indexes
Visit the Index page in our online documentation.
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Our eXtremeDB HTML documentation includes an extensive online library to introduce eXtremeDB. It will walk you through the installation process, and the use of key features.
Online DBMS documentation menu items include:
- The eXtremeDB Product Family
- eXtremeDB Supported Platforms
- What’s New in This Release
- Getting Started
- eXtremeDB Fundamental Concepts
- eXtremeDB User’s Guides
- Programming with eXtremeDB
- SQL Samples
- Review how eXtremeDB uses data indexes to boost performance