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jqGrid VS Apache Solr

Compare jqGrid VS Apache Solr and see what are their differences

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jqGrid logo jqGrid

Updated information on jqGrid.Can be used for free for personal, school or non-profit project, under the Creative Commons Attribution-Non-Commercial 3.0 License.

Apache Solr logo Apache Solr

Solr is an open source enterprise search server based on Lucene search library, with XML/HTTP and...
  • jqGrid Landing page
    Landing page //
    2022-04-04
  • Apache Solr Landing page
    Landing page //
    2023-04-28

jqGrid features and specs

  • Robust Features
    jqGrid offers a variety of features such as filtering, sorting, paging, and inline editing, which are essential for handling complex data operations within a grid.
  • Customizability
    Users can customize almost every aspect of the grid, including the user interface and functions, allowing for a tailored user experience that fits specific project needs.
  • Extensive Documentation
    jqGrid is accompanied by detailed documentation and numerous examples, making it easier for developers to learn and implement it effectively in their projects.
  • Cross-browser Compatibility
    The grid is compatible with most modern browsers, which ensures consistent performance and appearance across different user environments.
  • Large Community Support
    Due to its maturity and popularity, jqGrid has a large community, which provides a wealth of resources such as plugins, tutorials, and forums for troubleshooting.

Possible disadvantages of jqGrid

  • Complexity
    The extensive features and customization options can make jqGrid complex to set up and configure, especially for beginners.
  • Learning Curve
    Due to its comprehensive nature, there is a steep learning curve involved, which might require significant time investment to fully utilize all of jqGrid's capabilities.
  • Performance Issues with Large Data Sets
    Handling very large datasets can cause performance issues within the grid, potentially requiring additional optimization techniques like server-side paging.
  • Dependency on jQuery
    jqGrid is dependent on jQuery, which can be a disadvantage for projects aiming to minimize dependency on libraries for performance or size reasons.
  • Not Fully Free
    While there is a free version, the advanced features and components often require a commercial license, which could be a constraint for small or budget-constrained projects.

Apache Solr features and specs

  • Scalability
    Apache Solr is highly scalable, capable of handling large amounts of data and numerous queries per second. It supports distributed search and indexing, which allows for horizontal scaling by adding more nodes.
  • Flexibility
    Solr provides flexible schema management, allowing for dynamic field definitions and easy handling of various data types. It supports a variety of search query types and can be customized to meet specific search requirements.
  • Rich Feature Set
    Solr comes with a wealth of features out-of-the-box, including faceted search, result highlighting, multi-index search, and advanced filtering capabilities. It also offers robust analytics and joins support.
  • Community and Documentation
    Being an open-source project, Apache Solr has a strong community and comprehensive documentation, which ensures continuous improvements, updates, and extensive support resources for developers.
  • Integrations
    Solr integrates well with a variety of databases and data sources, and it provides REST-like APIs for ease of integration with other applications. It also has strong support for popular programming languages like Java, Python, and Ruby.
  • Performance
    Solr is built on top of Apache Lucene, which provides high performance for searching and indexing. It is optimized for speed and can handle rapid data ingestion and real-time indexing.

Possible disadvantages of Apache Solr

  • Complexity
    The initial setup and configuration of Apache Solr can be complex, particularly for those not already familiar with search engines and indexing concepts. Managing a distributed Solr installation also requires considerable expertise.
  • Resource Intensive
    Running Solr, especially for large datasets, can be resource-intensive in terms of both memory and CPU. It requires careful tuning and adequate hardware to maintain performance.
  • Learning Curve
    The learning curve for Apache Solr can be steep due to its extensive feature set and the complexity of its configuration options. New users may find it challenging to get up to speed quickly.
  • Consistency Issues
    In distributed setups, ensuring data consistency can be challenging, particularly for users unfamiliar with managing clustered environments. There may be delays or issues with synchronizing indexes across multiple nodes.
  • Maintenance
    Ongoing maintenance of a Solr instance, including monitoring, tuning, and scaling, can be labor-intensive. This requires dedicated effort to keep the system running efficiently over time.
  • Limited Real-time Capabilities
    Although Solr provides near real-time indexing, it may not be as effective as some specialized real-time search engines. For applications requiring truly real-time capabilities, additional solutions might be necessary.

Analysis of Apache Solr

Overall verdict

  • Yes, Apache Solr is generally considered a good option for organizations seeking a reliable, scalable, and flexible search platform. It offers extensive features and is supported by a strong community, making it a solid choice for many use cases.

Why this product is good

  • Apache Solr is highly regarded for its robust full-text search capabilities, scalability, and ease of integration. As an open-source search platform, it is built on Apache Lucene and provides powerful distributed search and indexing, replication, load-balanced querying, and automated failover and recovery. Solr is designed to handle large volumes of data efficiently and supports various data formats with powerful data management features.

Recommended for

    Apache Solr is recommended for organizations that need to implement powerful search capabilities, especially those managing large, complex datasets. It is ideal for businesses that require full-text search features, e-commerce sites, content management systems, and big data applications that demand high query performance and scalability.

jqGrid videos

+ Add

Advanced Grids in Salesforce Lightning Communities Using jqGrid

More videos:

  • Review - Sample CRUD With JQGrid (Part I)
  • Review - APEX jqGrid Integration

Apache Solr videos

+ Add

Solr Index - Learn about Inverted Indexes and Apache Solr Indexing

More videos:

  • Review - Solr Web Crawl - Crawl Websites and Search in Apache Solr

Category Popularity

0-100% (relative to jqGrid and Apache Solr)

jqGrid

Apache Solr

Data Grid
100 100%
Data Grid
0% 0
Custom Search Engine
0 0%
Custom Search Engine
100% 100
JavaScript Tools
100 100%
JavaScript Tools
0% 0
Custom Search
0 0%
Custom Search
100% 100

User comments

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Reviews

These are some of the external sources and on-site user reviews we've used to compare jqGrid and Apache Solr

jqGrid Reviews

We have no reviews of jqGrid yet.
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Apache Solr Reviews

Top 10 Site Search Software Tools & Plugins for 2022
Apache Solr is optimized to handle high-volume traffic and is easy to scale up or down depending on your changing needs. The near real-time indexing capabilities ensure that your content remains fresh and search results are always relevant and updated. For more advanced customization, Apache Solr boasts extensible plug-in architecture so you can easily plug in index and...
Source: influencermarketinghub.com
5 Open-Source Search Engines For your Website
Apache Solr is the popular, blazing-fast, open-source enterprise search platform built on Apache Lucene. Solr is a standalone search server with a REST-like API. You can put documents in it (called "indexing") via JSON, XML, CSV, or binary over HTTP. You query it via HTTP GET and receive JSON, XML, CSV, or binary results.
Source: vishnuch.tech
Elasticsearch vs. Solr vs. Sphinx: Best Open Source Search Platform Comparison
Solr is not as quick as Elasticsearch and works best for static data (that does not require frequent changing). The reason is due to caches. In Solr, the caches are global, which means that, when even the slightest change happens in the cache, all indexing demands a refresh. This is usually a time-consuming process. In Elastic, on the other hand, the refreshing is made by...
Source: greenice.net
Algolia Review – A Hosted Search API Reviewed
If you’re not 100% satisfied with Algolia, there are always alternative methods to accomplish similar results, such as Solr (open-source & self-hosted) or ElasticSearch (open-source or hosted). Both of these are built on Apache Lucene, and their search syntax is very similar. Amazon Elasticsearch Service provides a fully managed Elasticsearch service which makes it easy to...
Source: getstream.io

Social recommendations and mentions

Based on our record, Apache Solr seems to be more popular. It has been mentiond 19 times since March 2021. We are tracking product recommendations and mentions on various public social media platforms and blogs. They can help you identify which product is more popular and what people think of it.

jqGrid mentions (0)

We have not tracked any mentions of jqGrid yet. Tracking of jqGrid recommendations started around Mar 2021.

Apache Solr mentions (19)

  • List of 45 databases in the world
    Solr — Open-source search platform built on Apache Lucene. - Source: dev.to / 11 months ago
  • Considerations for Unicode and Searching
    I want to spend the brunt of this article talking about how to do this in Postgres, partly because it's a little more difficult there. But let me start in Apache Solr, which is where I first worked on these issues. - Source: dev.to / 11 months ago
  • Swirl: An open-source search engine with LLMs and ChatGPT to provide all the answers you need 🌌
    Using the Galaxy UI, knowledge workers can systematically review the best results from all configured services including Apache Solr, ChatGPT, Elastic, OpenSearch, PostgreSQL, Google BigQuery, plus generic HTTP/GET/POST with configurations for premium services like Google's Programmable Search Engine, Miro and Northern Light Research. - Source: dev.to / over 1 year ago
  • Looking for software
    Apache Solr can be used to index and search text-based documents. It supports a wide range of file formats including PDFs, Microsoft Office documents, and plain text files. https://solr.apache.org/. Source: about 2 years ago
  • 'google-like' search engine for files on my NAS
    If so, then https://solr.apache.org/ can be a solution, though there's a bit of setup involved. Oh yea, you get to write your own "search interface" too which would end up calling solr's api to find stuff. Source: over 2 years ago
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What are some alternatives?

When comparing jqGrid and Apache Solr, you can also consider the following products

ZingGrid - Built using web components, ZingGrid is a fully-featured, native solution for interactive, mobile-friendly JavaScript data grids and tables.

ElasticSearch - Elasticsearch is an open source, distributed, RESTful search engine.

AG Grid - The best HTML5 datagrid in the world

Algolia - Algolia's Search API makes it easy to deliver a great search experience in your apps & websites. Algolia Search provides hosted full-text, numerical, faceted and geolocalized search.

Handsontable - JavaScript Spreadsheet

Typesense - Typo tolerant, delightfully simple, open source search 🔍

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