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Databases
Related Topic: Faceted Search and Data Classification
SQL, NoSQL, Disk Images, Data Streams and Other Non-File Data
- The dtSearch Engine DataSource API supports indexing of SQL-type databases, NoSQL-type databases, disk images, network data streams, etc.
- Developers, please start with the first article under Databases and Field Searching at Selected Articles by Subject.
- Please also review all of the other articles under the Databases and Field Searching section of Selected Articles by Subject.
- Topics include faceted search, advanced data classification and much more.
- A “Getting Started” database indexing tutorial is also available among the I-Programmer articles.
I‑Programmer dtSearch and C# series:
• “Getting Started” • “Threading” • “Hit Highlighting” • “Database Indexing” • “Document Caching” - See also caching for faster access to remote databases.
SharePoint
The dtSearch product line can index SharePoint data in multiple ways:
- SharePoint makes is possible to replicate content locally. Please see these Microsoft articles for information on maintaining local folders with content from SharePoint.
- Sync SharePoint and Teams files with your computer - Microsoft Support
- Copy or move library files by using Open with Explorer - Microsoft Support (for older versions of SharePoint) - Any content that is stored in the file system can be indexed like any other folders using any dtSearch products (including dtSearch Desktop/Network/Web).
- Use the dtSearch Spider (available as an "off the shelf" component in dtSearch Desktop/Network/Web). Note: some authenticated SharePoint content may require API access.
- dtSearch Engine developers can also use the .NET Spider API. More information
- For maximum flexibility, dtSearch Engine developers can also use the dtSearch Engine DataSource API.
CodeProject: dtSearch's "DataSource API for indexing SharePoint Site Collections" - See also caching for faster access to remote databases.
Caching
dtSearch products also include a caching option for use with web-based or other remote data, or for faster generation of search reports.
Cache document text in the index. Storing the text of documents makes generation of search reports much faster, including generation of the brief hits-in-context synopsis in search results.
Cache documents in the index. Storing complete documents is useful in situations where the documents may not be accessible at search time, or where access to the documents may be slow or unreliable.