Apache Solr

83
65
+ 1
0
Milvus

5
12
+ 1
1
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Apache Solr vs Milvus: What are the differences?

Developers describe Apache Solr as "An open source search platform". 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. On the other hand, Milvus is detailed as "An Open Source Vector Similarity Search Engine". It is an open source similarity search engine for massive-scale feature vectors. Built with heterogeneous computing architecture for the best cost efficiency. Searches over billion-scale vectors take only milliseconds with minimum computing resources.

Apache Solr and Milvus can be primarily classified as "Search Engines" tools.

Milvus is an open source tool with 1.04K GitHub stars and 217 GitHub forks. Here's a link to Milvus's open source repository on GitHub.

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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 Milvus?

    It is an open source similarity search engine for massive-scale feature vectors. Built with heterogeneous computing architecture for the best cost efficiency. Searches over billion-scale vectors take only milliseconds with minimum computing resources.
    What companies use Apache Solr?
    What companies use Milvus?
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      What tools integrate with Apache Solr?
      What tools integrate with Milvus?

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      What are some alternatives to Apache Solr and Milvus?
      Splunk
      It provides the leading platform for Operational Intelligence. Customers use it to search, monitor, analyze and visualize machine data.
      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.
      Elasticsearch
      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
      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.
      See all alternatives
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