Name: Apache Solr
Rating: 8.7 (44 reviews)
Author: Apache

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### Indexing and Query Optimization
Users generally appreciate Apache Solr's robust search functionality and efficient query capabilities. The consensus among reviewers is that Apache Solr excels in indexing and query optimization, providing fast and accurate search results. Users highlight the ease of integration with various projects and the scalability features that enhance the overall search experience. While some users mention minor complexities in understanding the tool, the majority find Apache Solr to be a reliable solution for storing, indexing, and retrieving data efficiently.

### Search Engine Technologies
Users unanimously praise Apache Solr's search engine capabilities. They highlight its stability, fast query results, resilience in indexing, and ease of integration with other projects. Reviewers emphasize that Apache Solr excels in full-text search and Lucene query search, making it a top choice for various enterprise applications. Additionally, users appreciate Solr's high-speed search, scalability features, and robust indexing process, which minimizes indexing issues. Despite some recommendations for Elasticsearch for faster deployment, Apache Solr remains a solid choice for optimizing search engine performance through advanced search indexer techniques.

### Scalability and Performance
While users appreciate Apache Solr's scalability and performance in handling large volumes of data, some express concerns about its ability to keep up with the demands of cloud computing. The consensus leans towards acknowledging Solr's strength in providing high-speed search capabilities and resilient indexing processes. However, there are suggestions for improvements, such as the integration of a more robust JavaScript library or a data grid to enhance the search and display functionalities for millions of records. Despite these reservations, Apache Solr remains a popular choice for its efficient search and query optimization features.

### Data Integration and Management
Users consistently praise Apache Solr for its efficient data integration and management functionalities, highlighting its ability to easily integrate with APIs and databases, as well as its quick retrieval and indexing capabilities. The platform's features such as delta query, schema definitions, and document sharding are lauded for enhancing data organization and accessibility. Additionally, users find Apache Solr user-friendly and effective in handling complex data structures, making it a valuable tool for data management tasks.

### API and Integration Tools
Users have expressed mixed feelings about Apache Solr's integration capabilities. While some appreciate its ease of integration with APIs and CSV, others have highlighted the absence of an inbuilt JavaScript library or a data grid for handling large datasets efficiently. The need for a comprehensive grid widget or tool to manage and display millions of records remains a common concern among users. Despite its strengths in delta query, quick retrieval, and schema definitions, there are reservations about the scalability of Apache Solr in handling massive amounts of data efficiently.

### Clustering and Sharding
Opinions on Apache Solr's clustering and sharding features vary among users. While some reviewers praise the clustering and document sharding capabilities as excellent and wonderful features, others highlight the ease of use and understanding of Apache Solr, emphasizing its dynamic clustering and database integration. The consensus seems to be that clustering and sharding play a significant role in enhancing the search data representation and overall functionality of Apache Solr.

Users have provided several recommendations for using Solr in various business aspects. One of the most common recommendations is to leverage Solr's capabilities for storing and indexing data from different sources, allowing users to easily search and retrieve information. Another common recommendation is to take advantage of the quick learning curve, easy client-side coding, and straightforward setup of Solr. Users also recommend using Solr for searching massive amounts of data as it offers efficient performance and scalability. In addition, some users suggest using the latest version of Solr to benefit from its improved features and enhancements. Furthermore, users recommend considering both Elasticsearch and Solr to determine which one best suits their specific access methods and query requirements. Lastly, users find Solr useful for real-time search functionality, including word or partial word search, word synonyms, and the cost-effectiveness it offers.

Difficult Configuration: Several users have reported that they found the platform to be challenging to configure, particularly in terms of its ease of use. They have encountered difficulties while setting up and customizing the platform according to their needs.

Lack of Developer Community Understanding: Some reviewers have mentioned that they faced challenges in finding talent or developers who were well-versed with the platform. The lack of understanding within the developer community has made it harder for users to find suitable resources or support for their projects.

Slow Development on Drupal 8 Integration APIs: Users have expressed frustration with the slow progress in developing APIs for integrating the platform with Drupal 8. Specifically, they highlighted issues related to Apache Solr usage and integration, which impacted their ability to leverage the full potential of both platforms effectively.

Solr, an open-source search platform, has been widely used across various industries for its versatile capabilities. Users have found Solr to be an effective indexing mechanism for complex product data and user profiles, enabling rapid delivery of search results with minimal strain on hardware configurations. For example, a CTO at a real estate company implemented Solr in a Drupal powered e-commerce environment, resulting in remarkable success with the open-source integration. Additionally, Solr has been chosen as a NoSQL database for real estate search engines, managing vast amounts of classifieds and doubling the number of unique users.

Solr's functionality extends beyond e-commerce applications. It serves as a reliable search server in diverse projects such as city-wide websites, enterprise search functions, and internal company portals. By utilizing Solr, these platforms are able to deliver quick, accurate, and relevant search results to their users. Furthermore, Solr has transformed the retail domain by solving type-ahead search challenges and offering various faceting options that allow customers to quickly isolate their desired products.

The versatility of Solr is also evident in its application within the realm of venue data analysis and management. By implementing Solr in web portals that contain large collections of venue data, users can benefit from geospatial filtering and ease of use when searching and analyzing this information. In addition, Solr has proven to be an invaluable tool in e-commerce applications for product display, sorting, and management by facilitating easy querying and fetching of desired results.

Overall, Solr's ability to handle complex data indexing tasks and deliver fast search results has made it a popular choice for organizations across industries. Its versatility makes it suitable for various use cases ranging from enterprise search functions to retail domains and beyond.

Fast Performance: Many reviewers have praised the platform for its fast performance. They have found it impressive and appreciated the ability to rapidly grow their environments to meet expanding business needs. 

Flexibility of Solr: Users have mentioned that Solr is highly flexible and can be customized to meet specific business needs. They have been able to make Solr bend to their requirements, which they found advantageous.

Useful Functionality: Reviewers have emphasized the usefulness of Solr's faceted navigation and field collapsing/grouping functionalities. These features allow them to filter and obtain quick results for their websites, resulting in good and efficient outcomes for their customers.

Apache Solr is an open-source enterprise search server.

Elasticsearch is an enterprise search tool from Elastic in Mountain View, California.

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Enterprise search is the organized retrieval of structured and unstructured data within an organization. Enterprise search creates an easily navigated interface for entering, categorizing and retrieving data securely, in compliance with security and data retention regulations. Products in this category can be made available to customers, partners or employees.

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The Apache Software Foundation provides support for the Apache community of open-source software projects. The Apache projects are characterized by a collaborative, consensus based development process, an open and pragmatic software license, and a desire to create high quality software that leads the way in its field.

We consider ourselves not simply a group of projects sharing a server, but rather a community of developers and users.

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We use Apache Solr in different cases. The most usual is for index and searching, and it do it great! The accuracy is impressive. The other case is for caching some information and keep it worm. This case is very helpfull when some information do not need constant update and can be retrived from get requests.

Search indexes
Information caching
Databse rebuild

Memory consumption
Read and write operations
Load balancing for multiples sources

Very hard to find qualified professionals
Demands good infrastructure for hosting
Not easy to deploy it

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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.

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.

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.

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

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We use Solr as the search engine for our new city-wide website that we're building using the Drupal open source content management system. We want to make it easy for citizens to find the city services and information that they're seeking and search is a critical feature. We need it to deliver quick, accurate, and relevant results.

Solr is very flexible and can be customized to meet your specific needs and requirements.
Solr is fast at returning search results.
Solr is pretty much an industry standard so there's a good chance other software programs have modules designed to work with it.

It has a steep learning curve. It's not intuitive how to configure it or customize it.
It doesn't include a web crawler. Indexing your website requires adding a separate web crawler or using their API to add information to the index.
Debugging and troubleshooting query issues can be a difficult task.

It's enabled us to deliver fast, relevant search results on our new website. The site is still in beta and being actively developed so our complete ROI is still unknown.
It integrates very well with Drupal so it has saved us from having to develop a custom solution.

Apache Solr

Overview

What is Apache Solr?