Amazon OpenSearch Service vs Solr comparison

Amazon Web Services (AWS) and Apache are both solutions in the Search as a Service category. Amazon Web Services (AWS) is ranked #2 with an average rating of 7.4, while Apache is ranked #8. Amazon Web Services (AWS) holds a 5.4% mindshare in SS, compared to Apache’s 6.1% mindshare. Additionally, 92% of Amazon Web Services (AWS) users are willing to recommend the solution, compared to 100% of Apache users who would recommend it.

Amazon OpenSearch Service

Read 12 Amazon OpenSearch Service reviews

3,841 Views
845 Comparison Views

92% willing to recommend

Solr

Read 4 Solr reviews

585 Views
585 Comparison Views

100% willing to recommend

Amazon OpenSearch Service

Solr

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Executive SummaryUpdated on Aug 11, 2025

Solr and Amazon OpenSearch Service compete in search and analytics. Amazon OpenSearch Service holds a stronger position due to its flexibility and integration capabilities, while Solr's appeal lies in its competitive pricing and support.

Features: Solr provides powerful full-text search capabilities, customization options, and advanced search solutions. Amazon OpenSearch Service offers seamless scalability, integration with AWS, and comprehensive cloud-based solutions.

Room for Improvement: Solr could enhance integration with cloud services, simplify its deployment process, and improve real-time data processing capabilities. Amazon OpenSearch Service could focus on reducing costs, increasing customization options for dashboards, and offering more comprehensive offline access features.

Ease of Deployment and Customer Service: Solr, as an open-source option, requires more manual setup but benefits from extensive documentation and community support. In contrast, Amazon OpenSearch Service provides a managed experience that simplifies deployment with AWS's strong customer service.

Pricing and ROI: Solr's open-source nature provides a cost-effective solution for budget-conscious businesses, enhancing ROI. On the other hand, Amazon OpenSearch Service, despite higher upfront costs, offers greater ROI by leveraging cloud capabilities and reducing operational burdens.

To learn more, read our detailed Search as a Service Report (Updated: July 2025).

Buyer's Guide

Search as a Service

July 2025

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Helped 865,164 peers since 2012

Review summaries and opinions

We asked business professionals to review the solutions they use. Here are some excerpts of what they said:

Categories and Ranking

Amazon OpenSearch Service

Ranking in Search as a Service

2nd

Average Rating

7.6

Reviews Sentiment

7.2

Number of Reviews

Ranking in other categories

Application Performance Monitoring (APM) and Observability (25th), Log Management (20th)

Solr

Ranking in Search as a Service

8th

Average Rating

7.8

Number of Reviews

Ranking in other categories

No ranking in other categories

Mindshare comparison

As of August 2025, in the Search as a Service category, the mindshare of Amazon OpenSearch Service is 5.4%, down from 16.1% compared to the previous year. The mindshare of Solr is 6.1%, down from 6.2% compared to the previous year. It is calculated based on PeerSpot user engagement data.

Search as a Service

Featured Reviews

Johnny Suleiman

MS AWS expert at Bespin Global MEA, an e& enterprise Company

Scalability is a key feature as it allows easy scaling of the platform without downtime

OpenSearch is used as a search engine for specific logs, mainly in e-commerce and monitoring the logs themselves. It is very valuable for e-commerce, enabling data analysis on application logs and customer behavior, and can be integrated with other services, including AI and machine learning…

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reviewer823641

Senior Search Engineer at a financial services firm with 51-200 employees

The Natural Language Search capability is helpful and intuitive for our users

The initial setup is complex because this is a distributed system, and you have to make sure that every individual node is aware of every other node in existence. This search engine has a large capacity, so you need to make sure that there is enough buffer space. We took one month to deploy and perform a fresh setup. Our strategy was to start with a local data center, before venturing into cross data center replicas. A staff size of two to four people is suitable for deploying and maintaining the solution, depending upon the scale. They would set up the solution and put monitoring in place for the indexing jobs, as well as design the schema so that the data can feed well.

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Quotes from Members

We asked business professionals to review the solutions they use. Here are some excerpts of what they said:

Pros

"They have the good documentation in the help text and that is the reason the Amazon is the perfect solution in the current market."

"I would definitely recommend Amazon OpenSearch Service to other professionals due to its fast and reliable search capabilities."

"The most valuable features of Amazon Elasticsearch are ease of use, native JSON, and efficiency. Additionally, handles many use cases and search grammar was useful."

"The initial set up is very easy...We really appreciate Amazon!"

"Amazon OpenSearch Service has enhanced our organization's ability to store and search large amounts of data efficiently."

"We retrieve historical data with just a click of a button to move it from cold to hot or warm because it's already stored in the backend storage"

"The customer service is excellent, rated nine out of ten."

"Regarding valuable features of the solution, we found with the process, which we have used in both cases where we used the solution that while you're seeing the streaming of data, you can analyze in the initial phase what sort of data you are streaming and whether it is valuable."

More Amazon OpenSearch Service pros

"One of the best aspects of the solution is the indexing. It's already indexed to all the fields in the category. We don't need to spend so much extra effort to do the indexing. It's great."

"It has improved our search ranking, relevancy, search performance, and user retention."

"Sharding data, Faceting, Hit Highlighting, parent-child Block Join and Grouping, and multi-mode platform are all valuable features."

"The most valuable feature is the ability to perform a natural language search."

Cons

"One improvement I would like to see is support for auto-scaling."

"It would be beneficial to have some level of customization available in the managed service, tailored to the specific use cases of the end users."

"We faced documentation challenges during integration after migrating from Elasticsearch to Amazon OpenSearch Service. Better documentation on integration, query handling, and a more user-friendly UI could enhance the product."

"There is a problem with the database. Amazon only provides the hosting to run our applications bias, but there is no option to manage the database within the Elasticsearch product."

"In terms of data handling capabilities with Amazon OpenSearch Service, they can be complex and managing data in comparison to other SIM solutions is a major drawback, as it is very hard to handle the data."

"I would say that, basically, the configuration part is an area with a shortcoming...Some upgradation is required on the configuration side so that we can get to use it."

"They can enhance data visualization."

"The pricing aspect is a concern. The service is way too costly. For the past month, I used only 30 to 40 MB of data, and the cost was $500. AWS could improve pricing."

More Amazon OpenSearch Service cons

"With increased sharding, performance degrades. Merger, when present, is a bottle-neck. Peer-to-peer sync has issues in SolrCloud when index is incrementally updated."

"Encountered issues with both master-slave and SolrCloud. Indexing and serving traffic from same collection has very poor performance. Some components are slow for searching."

"It does take a little bit of effort to use and understand the solution. It would help us a lot if the solution offered up more documentation or tutorials to help with training or troubleshooting."

"SolrCloud stability, indexing and commit speed, and real-time Indexing need improvement."

"The performance for this solution, in terms of queries, could be improved."

Pricing and Cost Advice

"You only pay for what you use."

"The solution is not expensive, but priced averagely, I will say."

"Compared to other cloud platforms, it is manageable and not very expensive."

"There is a community edition available and the price of the commercial offering is reasonable."

"The only costs in addition to the standard licensing fees are related to the hardware, depending on whether it is cloud-based, or on-premise."

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Top Industries

By visitors reading reviews

Financial Services Firm

16%

Computer Software Company

13%

Manufacturing Company

Government

Computer Software Company

15%

Retailer

Manufacturing Company

Financial Services Firm

Company Size

By reviewers

Large Enterprise

Midsize Enterprise

Small Business

No data available

Questions from the Community

What do you like most about Amazon OpenSearch Service?

We retrieve historical data with just a click of a button to move it from cold to hot or warm because it's already stored in the backend storage

See all answers

What is your experience regarding pricing and costs for Amazon OpenSearch Service?

I would consider the pricing as a six based on how much data we are handling; if we handle minimal data, it's cheap, but for large data, it becomes costly. Our clients usually pay between $1,000 to...

See all answers

What needs improvement with Amazon OpenSearch Service?

In terms of data handling capabilities with Amazon OpenSearch Service, they can be complex and managing data in comparison to other SIM solutions is a major drawback, as it is very hard to handle t...

See all answers

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Comparisons

Grafana Loki vs Amazon OpenSearch Service

Compared 26% of the time

Datadog vs Amazon OpenSearch Service

Compared 13% of the time

Amazon CloudWatch vs Amazon OpenSearch Service

Compared 11% of the time

Dynatrace vs Amazon OpenSearch Service

Compared 5% of the time

New Relic vs Amazon OpenSearch Service

Compared 4% of the time

More Amazon OpenSearch Service Competitors

Elastic Search vs Solr

Compared 29% of the time

Algolia vs Solr

Compared 21% of the time

Azure AI Search vs Solr

Compared 21% of the time

Amazon AWS CloudSearch vs Solr

Compared 19% of the time

Amazon Kendra vs Solr

Compared 10% of the time

More Solr Competitors

Product Reports

Buyer's Guide

Amazon OpenSearch Service

August 2025

Download Amazon OpenSearch Service product report

Buyer's Guide

Search as a Service

July 2025

Download Solr product report

Also Known As

Amazon Elasticsearch Service

No data available

Overview

Amazon OpenSearch Service provides scalable and reliable search capabilities with efficient data processing, supporting easy domain configuration and integration with numerous systems for enhanced performance.

Amazon OpenSearch Service offers advanced features for handling JSON, diverse search grammars, quick historical data retrieval, and ultra-warm storage. It also includes customizable dashboards and seamless tool integration for large enterprises. With its managed infrastructure, OpenSearch Service supports efficient system analysis and business analytics, improving overall performance and flexibility. Despite these features, areas like configuration complexity, lack of auto-scaling, and integration with Kibana require attention. Users seek enhanced documentation, better pricing options, and more flexible data handling. Desired improvements include default filters, mapping configuration, and alerting capabilities. Enhanced data visualization and Compute Optimizer Service integration are also recommended for future updates.

What features define Amazon OpenSearch Service?

Scalable Search: Offers reliable search capabilities across vast datasets.
JSON Handling: Supports efficient management of JSON data.
Ultra-warm Storage: Enables cost-effective historical data retrieval.
Dashboard Customization: Supports tool integration and tailored visuals.
System Upgrades: Allows for seamless infrastructure upgrades.

What benefits and ROI should users consider?

Performance Enhancement: Significant improvement in search and data retrieval.
Cost-Effectiveness: Provides a cloud-native solution optimized for AWS environments.
Comprehensive Analytics: Delivers detailed insights for business applications.

Amazon OpenSearch Service is utilized in various industries for log management, data storage, and search capabilities. It supports infrastructure and embedded management, analyzing logs from AWS Lambda, Kubernetes, and other services. Companies use it for application debugging, monitoring security and performance, and customer behavior analysis, integrating it with tools like DynamoDB and Snowflake for a cost-effective solution.

Amazon Web Services (AWS)

Solr is highly reliable, scalable and fault tolerant, providing distributed indexing, replication and load-balanced querying, automated failover and recovery, centralized configuration and more. Solr powers the search and navigation features of many of the world's largest internet sites.

Apache

Sample Customers

VIDCOIN, Wyng, Yellow New Zealand, zipMoney, Cimri, Siemens, Unbabel

eHarmony, Sears, StubHub, Best Buy, Instagram, Netflix, Disney, AT&T, eBay, AOL, Bloomberg, Comcast, Ticketmaster, Travelocity, MTV Networks

Find out what your peers are saying about Elastic, Amazon Web Services (AWS), Algolia and others in Search as a Service. Updated: July 2025.

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We monitor all Search as a Service reviews to prevent fraudulent reviews and keep review quality high. We do not post reviews by company employees or direct competitors. We validate each review for authenticity via cross-reference with LinkedIn, and personal follow-up with the reviewer when necessary.