Item: Apache Solr
Rating: 8
Author: trang nguyen

Overall Satisfaction with Apache Solr

Use Cases and Deployment Scope

We use Solr as a search server in our eCommerce project which our product data is stored as documentation. Solr works as both a data store server and search indexer. It provides a very high-speed query to respond almost immediately in milliseconds, allowing us to support the TypeAhead function to our end user.

Pros and Cons

Pros

Flexible and powerful query language allows us to build a various and complex query to retrieve data.
High-speed response query.
Good documentation and great community support.
Cluster mode with separate master and slave so we could scale each type base on we need to increase input data or response speed.

Cons

It does not support authentication and authorization so we need to place it inside a private network.
Working with Solr cloud require additional Zookeeper.
Master node requires reconfiguration if it down.

Return on Investment

Increase our overall product performance.
Sped up our development time as Solr given effective and simple query.
Decreases our deployment time.

Alternatives Considered

We have considering AWS search and Elastic search but decide to go with Solr as we need high speed and flexible query, and so far it meets all our requirement so we still continue with Solr.

Other Software Used

Apache Tomcat, Oracle Java SE, JMeter, Selenium, Gitlab, Jenkins, Redis

Likelihood to Recommend

Solr is suitable in almost every case for Indexing and Searching data, but If you need to expose your Solr server to the external network, you need to integrate with another authentication solution. Reviewing your business on input and response data to define a good strategy for Master and Slaver Nodes will save cost and increase system performance.

Solr would not fit if you want a data warehouse for storing data in binary or unstructured data.

Comments

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Powerful, fast and flexible search tool with a rich query API set