Found 131 packages
The Official Couchbase .NET SDK.
The official Language Integrated Query (LINQ) provider for querying Couchbase Server with N1QL using the Couchbase .NET SDK 3.4 and greater.
Extensions for CouchbaseNetClient 3.x supporing .NET Core configuration and dependency injection.
A lightweight, document-oriented (NoSQL), syncable database engine for .NET
Couchbase client extensions
ASP.NET Full Framework SessionState and OutputCache Providers for Couchbase .NET SDK
This package provides functionality for Couchbase Distributed ACID Transactions for .NET Core. Distributed ACID Transactions are operations that ensure that when multiple documents need to be modified such that only the successful modification of all justifies the modification of any, either all the modifications do occur successfully; or none of them occurs. This Atomicity supports insert, update, and delete operations, across any number of documents.
A custom ASP.NET Core Middleware plugin for distributed cache using Couchbase server as the backing store. Supports both Memcached (in-memory) and Couchbase (persistent) buckets.
A lightweight, document-oriented (NoSQL), syncable database engine for .NET
Package Description
A simple component that extends Couchbase.Lite to provide extension methods for converting an object to a Document/MutableDocument and a Document/MutableDocument to an object. This package is not officially supported by Couchbase Inc.
A lightweight, document-oriented (NoSQL), syncable database engine for .NET
A lightweight, document-oriented (NoSQL), syncable database engine for .NET
A lightweight, document-oriented (NoSQL), syncable database engine for .NET
Package Description
Contains CouchbaseDistributedCache that implements IDistributedCache interface
A lightweight, document-oriented (NoSQL), syncable database engine for .NET
Interfaces for making extensions to Couchbase Lite .NET
Serilog event sink that writes to a Couchbase cluster using the Couchbase .NET client library.
Provides extensions for ICouchbaseCollection to perform multiple similar operations in parallel. For example, getting 100 documents based on their keys or performing a bulk insert of 100,000 documents. It is optimized to maximize throughput by limiting the degree of parallelization and to returning exceptions separately for each operation.