The super fast, super simple real time dimensional aggregator for high performance analytics and reporting in .NET

Dagger version released!

This new version has a lot of new improvements and features and has included much work on expanding the automated test code base even further, ensuring robustness and stability - taking a large step closer to a production ready release.

Compressed Bitmap indexes.

The bit map indexes are now compressed on the fly leading to lower memory usage and faster queries.

New format when committing transactions

In previous versions all communication between client and server was done in Json-format. This was fast but could get a lot faster especially when committing transactions where the highest thoughput is needed. In this new version most communication is still in Json but now using the Json.Net serializer, the transactions / inserts on the other hand are now by default serialized in a highly optimized binary format giving up to twice as fast insert / commit performace. The previous Json serializer also created a lot of internal instances during serialization wich led to unneccesary memory usage and much garbage collector overhead.

Optimizations for the count measure

The simple record count measure has been highly optimized and now uses only the bitmap indexes to calculate its value leading to a great increase in speed.

Calculated Measures

The latest version now includes calculated measures, starting with a simple calculated measure for averages. Regular measures are the most basic measures like sum, max, min and are calculated on a per record basis in realtime or saved as aggregates. Calculated measures are more dynamic measures that uses the regular measures to calculate their values. In this version averages are supported, in coming versions there will be more calculated measures by default as well as the posibillity to create custom caluclated measures for your business case.

Various performance optimizations

A lot of various performance improvements have been made giving faster inserts, queries and start-up time.

Stability and robustness

A lot of new unit-tests have been built to ensure correctnes, stability and robustness. This includes automated tests with static and random sample data as well as data from different real-world test cases


Improved user interface for creating cubes and improved table for query results.