Linkurious Enterprise 2.10, “incremental indexing” comes with its own native option to synchronize data from Neo4j to Elasticsearch. Incremental indexing was initially introduced in the 2.10 beta release and now meets our quality standards, making it production-ready.
For a search engine to function, it needs an up-to-date index. In the case of Linkurious Enterprise, this index needs to be synchronized with the content of a graph database. AzureSearch and Neo4jSearch are native search options for CosmosDB and Neo4j respectively, and they provide this synchronization out of the box.
Neo4j can also be used together with Elasticsearch. When using Elasticsearch as the search solution, this synchronization needs to be provided. Until 2.9 we relied on a plugin called “Neo4j-to-Elasticsearch” that was responsible for propagating changes from Neo4j to Elasticsearch.
The use of the Neo4j-to-Elasticsearch involved downloading and configuring the plugin, which was an error-prone task. To make this process smoother and more robust, Linkurious Enterprise 2.10 introduces a built-in incremental indexing option.
With incremental indexing enabled, the content of the graph database is synchronized at the time interval of your choice, sending to Elasticsearch the information about the data that has changed since the last run of incremental indexing. For example, if the synchronization is planned every night at midnight, only the data modified over the last 24 hours will be sent to Elasticsearch.
New nodes or edges, new properties or modified property values are therefore available for search immediately after the next incremental indexing run is finished.
To learn how to set up Incremental indexing go to our documentation.