A More Powerful Way to Manage Data for .NET

The ComponentOne DataEngine uses in-memory caching technology to deliver faster extraction, transformation, and loading (ETL) of large and complex data sets.

  • Fetch and query millions of records in less than a second
  • Sort, filter, group, and aggregate data at runtime without needing to hit the server
  • Combine data from multiple data sources into a single collection
  • Supports .NET Standard, .NET Framework, .NET 5, and .NET 6

DataEngine is part of ComponentOne Data Services Edition.

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Why Choose ComponentOne DataEngine for Your .NET Applications?

Analyze Large Unstructured Data Sets

Import any dataset that can be converted into an IEnumerable and take advantage of DataEngine's high-performance, column-oriented architecture to construct analytical queries.

Blend Data From Multiple Sources

Combine data from multiple data sources (including SQL Server, CSV, JSON, and collections of business objects) into a single, queryable collection of objects in your C# code.

Self-Contained Analytics

Provide analytics locally within your application without requiring external tools such as PowerBI. DataEngine is a small footprint C# library that can be used in any .NET application.

.NET DataEngine Key Features

Fast Query Performance

ComponentOne DataEngine is a standalone .NET library that delivers high-performance analytics for large datasets. Its column-oriented storage model uses memory-mapped files to provide exceptional performance, often processing millions of records in a second or less.

Instant Data Analysis

DataEngine provides quick analytics within your application by filtering, sorting, grouping and aggregating your datasets at runtime using various query operations. With the DataEngine Workbench tool you can load transformed data and analyze it to obtain quick insights.

Efficiently Query Dates

Efficiently query against date and time information by extracting only relevant parts of the date, such as sorting by year. You can also aggregate data by useful functions like YTD (year to date) and QTD (quarter to date) where summaries need to be created on period-to-date.

Blend Data from Multiple, Disparate Data Sources

ETL processes often need to integrate data from multiple sources, such as SQL Server, CSV, or JSON. DataEngine provides mechanisms for gathering data from remote servers or local files, and then ties the data sources together using join queries. Get data from online sources like CRM, WorkFlow, or accounting systems using the ComponentOne DataConnectors..

Easy-to-Use Workbench Tool

Use the standalone DataEngine Workbench desktop app on Windows or Mac to create and visualize queries without coding, or use the command-line tool to make working with DataEngine easier. Further, the script and JSON generated by this tool can be used in JavaScript applications.

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