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Apache Solr vs Lucene: What are the differences?

# Introduction
This markdown provides a comparison between Apache Solr and Lucene, two popular search technologies used for information retrieval.

1. **Architecture**: Lucene is a Java-based search library that provides indexing and searching capabilities at a lower level, while Apache Solr is built on top of Lucene and provides a more user-friendly, feature-rich search platform with additional functionalities such as full-text search, faceted search, and result highlighting. 
2. **Scalability**: Apache Solr is designed for high scalability and can handle large volumes of data efficiently through distributed indexing and querying, while Lucene is best suited for smaller-scale applications that do not require the same level of scalability.
3. **Ease of Use**: Apache Solr offers a more user-friendly interface and configuration options compared to Lucene, making it easier for developers to set up and customize search functionalities without needing to delve deep into the intricacies of the underlying search engine library.
4. **Management and Monitoring**: Apache Solr provides built-in tools for managing and monitoring search indexes, as well as monitoring performance metrics, whereas Lucene requires developers to implement their monitoring and management tools or rely on third-party solutions.
5. **Community Support**: Apache Solr has a larger and more active community compared to Lucene, resulting in frequent updates, bug fixes, and new features being added to the platform, ensuring better long-term support and development.
6. **Deployment Options**: Apache Solr can be deployed as a standalone server or as a part of a larger application stack, making it flexible for various use cases, while Lucene is typically embedded within an application, limiting deployment options.

In Summary, Apache Solr provides a more scalable, user-friendly, and feature-rich search platform compared to Lucene, making it the preferred choice for applications requiring advanced search functionalities and high scalability. 
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    What is Apache Solr?

    It uses the tools you use to make application building a snap. It is built on the battle-tested Apache Zookeeper, it makes it easy to scale up and down.

    What is Lucene?

    Lucene Core, our flagship sub-project, provides Java-based indexing and search technology, as well as spellchecking, hit highlighting and advanced analysis/tokenization capabilities.

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    What tools integrate with Apache Solr?
    What tools integrate with Lucene?

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    What are some alternatives to Apache Solr and Lucene?
    It provides the leading platform for Operational Intelligence. Customers use it to search, monitor, analyze and visualize machine data.
    Elasticsearch is a distributed, RESTful search and analytics engine capable of storing data and searching it in near real time. Elasticsearch, Kibana, Beats and Logstash are the Elastic Stack (sometimes called the ELK Stack).
    MongoDB stores data in JSON-like documents that can vary in structure, offering a dynamic, flexible schema. MongoDB was also designed for high availability and scalability, with built-in replication and auto-sharding.
    Apache Spark
    Spark is a fast and general processing engine compatible with Hadoop data. It can run in Hadoop clusters through YARN or Spark's standalone mode, and it can process data in HDFS, HBase, Cassandra, Hive, and any Hadoop InputFormat. It is designed to perform both batch processing (similar to MapReduce) and new workloads like streaming, interactive queries, and machine learning.
    Azure Search
    Azure Search makes it easy to add powerful and sophisticated search capabilities to your website or application. Quickly and easily tune search results and construct rich, fine-tuned ranking models to tie search results to business goals. Reliable throughput and storage provide fast search indexing and querying to support time-sensitive search scenarios.
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