RavenDB 2.5 with Dynamic Aggregation and Query Streaming
A stable version 2.5 of the document database RavenDB has been released with dynamic aggregation allowing for complex queries and an Unbounded results API using query streaming to retrieve large result sets in a single request.
The new features or improvements include:
- Dynamic aggregation allowing for much more complex queries compared to map/reduce indexes. This brings more options for reporting applications and allows for complex aggregation with additional filtering.
- An Unbounded results API that uses a query streaming model to make it possible to retrieve all items from a large result set with a single request without causing memory usage problems. This is done by creating a snapshot of what items to return and then using a return stream for returning all the items.
- Result Transformers for server side projections including the possibility to include data from other documents.
- Spatial Enhancements giving the ability to retrieve data based on spatial coordinates, e.g. finding all points within a specified distance from a given centre point.
- Excel integration with a CSV endpoint so that you can create an Excel file that automatically pulls data from a database.
- Write assurance giving the client API the ability to wait until a specified number of replication has completed.
- Indexes can be prioritized to control how much of the indexing process each index may use.
- A MSI Installer to simplify the installation process.
Improvements for operations include a simplified process for restoring databases and more endpoints for debug & analysis as well as more information to the existing endpoints.
RavenDB is a transactional, open-source document database written in .NET. Data is stored schema-less as JSON documents and can be queried using LINQ or the RESTful API with other tools.
RavenDB is released as open-source under the AGPL license, with several license options available.
The current stable version is 2.5.2666
John Krewson, Steve Ropa and Matt Badgley Nov 24, 2014