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James Terwilliger committed Dec 11, 2018
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322 changes: 26 additions & 296 deletions .gitignore
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21 changes: 21 additions & 0 deletions README.md
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This project has adopted the [Microsoft Open Source Code of Conduct](https://opensource.microsoft.com/codeofconduct/).
For more information see the [Code of Conduct FAQ](https://opensource.microsoft.com/codeofconduct/faq/) or
contact [[email protected]](mailto:[email protected]) with any additional questions or comments.

# Introduction

Trill is a high-performance one-pass in-memory streaming analytics engine from Microsoft Research. It can handle both real-time and offline data, and is based on a temporal data and query model. Trill can be used as a streaming engine, a lightweight in-memory relational engine, and as a progressive query processor (for early query results on partial data).

# Getting Started

1. Of course, the sources are right here!
2. You can get binaries from our [NuGet feed](https://www.nuget.org/packages/Trill/).

# Learn More

- The [Trill paper](http://research.microsoft.com/pubs/231690/trill-vldb2015.pdf) appeared at VLDB.
- The [Trill technical report](http://research.microsoft.com/pubs/214609/trill-TR.pdf).
- Additional documents located in the /Documentation directory:
- TrillQueryWritingGuide: introduces basic concepts of Trill query authoring
- Ingress: describes how data is ingressed into and egressed out of Trill
- TrillInternals: outlines Trill innovations and internals
- BestPractices: describes best practices low-memory real-time deployments
- HighAvailability: details Trill high-availability support
- UserDefinedAggregates: introduces a framework for query authors to create custom aggregates
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