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Alternatives to Adobe Search&Promote

Alternatives to Adobe Search&Promote. Learn about Search&Promote alternatives and top considerations for migration to a new site search solution.


Adobe Search&Promote is integrated into Adobe Target, a personalization solution that’s part of the Adobe Experience Manager CMS suite of tools. Adobe Target itself is a package of tools for personalizing web and shopping experiences.

Adobe Search&Promote is built on top of the venerable Apache Lucene search engine — the same search engine that powers Elasticsearch and Apache Solr.

One reason Adobe is phasing out Search&Promote is it’s acquisition of Magento in 2018. Adobe has stated that it intends to push Search&Promote e-commerce users towards Magento. For everyone else, they’re recommending Elasticsearch or Solr.

Another reason is that search engines have evolved considerably. Things such as machine learning or natural language processing (NLP) are expensive to add. Speed is a consideration, too, particularly for certain use cases such as e-commerce where speed and frequent index updates are important. Lucene-based search engines require extensive customization to meet newer work requirements such as these.

Like other similar stand-alone solutions, Search&Promote includes features for on-site search such as instant indexing, autocomplete (also called autosuggest), search merchandising, search facets and filters, synonyms, analytics, and more.

Its biggest selling point, however, is that it was built to integrate with Adobe Experience Manager, Adobe’s comprehensive content management suite. For Adobe customers, it was an obvious add-on that could be bundled with their AEM solution.

Adobe Experience Manager logo

Planning for migration

It’s likely that you have years of data and dozens if not thousands of customizations and rules already in place with your existing solution. Migrating to a new solution requires some planning. The good news is that many of the custom features that came with Search&Promote are standard in most of the newer alternatives. Some solutions also offer simpler ways to customize search that require less overhead and management.


There are two ways you can build a new search index: with a crawler or an API. A crawler will be very convenient for getting up and running quickly. However, if you have a particularly complex site, a lot of dynamic content, or need to index rich metadata — as is the case for e-commerce stores — you will want to consider using an API to map the AEM schema. Be sure to pick a solution that offers the best indexing option available for your site.

Filters and facets

You probably already have search filters and facets on your site. If not, now’s the time! But, assuming you do, you’ll want to pick a solution where you can quickly create new filters and test them to be sure you’re getting the same results (if not better) than before.

Relevance and ranking

Search&Promote included features to declare which fields to use for ranking and then had settings to adjust search relevance and ranking. When migrating to a new solution, you will want to recreate the rules as closely as possible. However, different solutions will have different algorithms and may still rank results differently.

You can accelerate the re-ranking if you select a newer solution with machine learning. AI-based search solutions can continuously improve search performance based on any number of desired outcomes such as CTR, signups, shopping cart activity, or sales.


You say “sneakers,” I say “running shoes.” Your users are typing in search terms that may be different from how your site is optimized. If you have already built a synonym library in Search&Promote, you’ll want to import it into whatever solution you select.

Autocomplete and typo tolerance

In old school search, users type in a query and hit return to see results. Consumers, however, expect at minimum a Google or Amazon-like search with suggestions, or autocomplete or autosuggest, as they type. Moreover, the search platform you choose should also include spelling correction or typo tolerance to handle misspelled words as users type out their query.

Search&Promote offered these features, but most newer solutions have them as well out-of-the-box.

Those are just a few of the considerations when migrating off of Search&Promote.

Search-as-a-service (SaaS) alternatives

For Search&Promote customers, a SaaS solution is the fastest way for Adobe customers to migrate to something new. There are many alternatives to Search&Promote. We’ve highlighted just a few below. is a site search engine built from the ground up for developers. It offers tremendous flexibility and ease of configuration built on top of a cloud-native architecture for elastic scale. Projects that can take weeks or months with other search solutions can be accomplished in hours or days on without the need for a battalion of engineers. Because it is fully-hosted and battle-tested with thousands of queries per second, you can spend more time working on your core business without having to manage search scale. approaches search differently from legacy search engines. Whereas Lucene-derivatives like Search&Promote have immutable search indexes, treats search more like a database, which offers some advantages in near real-time read/write speed and data synchronization. It also has built-in machine learning for continuous improvement of search performance.

Additionally, has taken a different approach to configuration and extensibility. Customers can customize search both at query time and during indexing. Configuration settings can be adjusted both through intuitive no-code relevance settings or, for more technical users, via YAML-based scripts called pipelines. You can use these configurations to re-create your Search&Promote rules, improve search performance, and even A/B test different algorithms to increase clicks and on-site conversions.

Core features, such as crawling, autocomplete, schema configuration, document indexing, synonyms, filters, faceted search, etc. are all baked in. In addition, offers a REST-like API for connecting to business data and Node, PHP, and Go SDKs, and React and JavaScript libraries for complete front-end customization.

Case Study: 100x ROI: features include:

  • Instant indexing with full-text crawler and APIs, including document (PDF, DOCX) search
  • Easy to add and configure advanced search capabilities such as typo tolerance, smart autosuggest, personalization, and AB testing via pipelines
  • User friendly drag and drop search design builder and ReactJS libraries
  • No re-indexing required for algorithm changes

Best use cases:

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Acquired by Elasticsearch in 2017, Swiftype is a simple, but powerful SaaS search solution. Swiftype was built on top of Elasticsearch for indexing and storing content. (Elasticsearch itself is built on top of Lucene which has certain limitations particularly as search indexes change.)

Unlike Elasticsearch which is built for engineering teams to create full-text search and log analytics solutions, Swiftype has a very good end-to-end site search user experience. Swiftype is a drop-in search solution. It can index a website either through a crawler or API, offers out-of-the-box support for cross domain indexing, spell checking, instant search, search overlay, autocomplete, and more.

Some reviewers have noted a lack of good PDF and document indexing options and have mentioned concerns around high pricing and hitting quota limits sooner than expected.

Swiftype features include:

  • Easy to use interface and fast set up and configuration
  • Detailed search analytics to uncover search trends and issues
  • Enterprise-level security (SOC2) and hosting options

Best use cases:

  • Site search
  • Publishing
  • Customer support


Coveo has built its own enterprise search technology that allows people to build secure, enterprise search applications and knowledge bases. With their tight coupling to SiteCore, Salesforce, ServiceNow, and other B2B enterprise applications and SQL and NoSQL databases, Coveo offers fast search across datastores for internal KBs and other enterprise use cases.

Coveo is not as general-purpose a search platform as or Swiftype. It’s a platform to ingest and transform different data types into searchable, accessible content with Coveo’s proprietary search, machine learning, and recommendations engines built on top. Reviewers have mentioned that initial indexing can be slow, that updates are equally slow and cumbersome, and the user experience and UI is average, but once your content is integrated into Coveo it can be a very powerful tool.

More recently, the company has acquired AI and e-commerce technology to extend its footprint into e-commerce use cases.

Coveo features include:

  • Machine learning-powered intelligent search
  • Recommendation and personalization features to deliver the right content faster to the right users across datastores
  • Native integrations with B2B services to provide comprehensive enterprise search

Best use cases:

  • Designed for mid-to-large enterprises with multiple systems and datastores to index
  • Backend search for internal knowledge base
  • E-commerce and site search


Lucidworks is an enterprise SaaS custom search solution built on top of Apache Solr, an open source search engine that’s powering thousands of enterprise search solutions. Effectively, customers get the power of Solr with a custom UI, APIs, and modules from Lucidworks.

Basic search features such as autocomplete and spell checking (what Lucidworks calls “query rewrites”) are premium features available for higher tier customers. If you’re looking for a professional services partner to help build a custom, powerful search solution, Lucidworks is worth a look.

Lucidworks features include:

  • Pre-built solutions for e-commerce, help desk, and knowledge management use cases
  • Lucidworks Fusion — personalized, federated search across enterprise datastores
  • Built-in NLP, categorization, and content clustering

Best use cases:

  • Large scale application and e-commerce search
  • Customer service
  • Knowledge base


Like, Algolia is a new search engine built from the ground up. Originally, Algolia was developed for mobile search use cases, but has since been extended to more traditional search projects. Algolia can boast about its retrieval speed; it’s milliseconds faster than the competition. Those few milliseconds won’t matter for most use cases, but if speed is important, Algolia is worth a look. As a fully-hosted product, Algolia also eliminates the need for cluster management.

Algolia has quickly grown into a major player because of how simple and easy it is to get started. It’s a great general purpose search engine. But, it has its critics too, particularly around pricing and complexity for managing custom rules and configurations. For example, anytime Algolia re-indexes the database — such as for A/B testing — it counts against monthly search queries quota. Features such as machine learning are add-ons that also cost more. It's ranking algorithm is a simple tie-breaking algorithm, which is easier to understand but also less flexible and powerful than other solutions on the market.

Algolia features include:

  • Instant indexing and full-text search
  • Global language support and advanced language processing
  • Fast information retrieval

Best use cases:

  • Website search
  • App search
  • Mobile search

Cloud alternatives

AWS, GCP, and Azure

The major cloud providers now offer many alternatives to Search&Promote including Microsoft’s Azure Cognitive Search, Amazon Cloudsearch, and Google Cloud Search. If you go the cloud provider route, you’re going to select the one your company is already working with.

Cloud providers offer both private and public hosted search solutions. If your app is hosted in one of these providers, then it might be worth considering them for your search service as well. Co-locating your search service with your app makes a lot of sense for reducing latency.

The pros and cons of each cloud service provider and software vary a lot. But they have some similarities:

  • They're built to scale, but still require a good deal of hand-holding
  • Each solution requires expertise and overhead for managing the search instance
  • They’re best suited if you want to co-locate search with your site or app

Unlike several of the alternatives mentioned above, cloud search solutions are not drop-in replacements. They require considerable configuration and are typically only managed by engineering teams. The reason we’re including them on this list is because they can offer tremendous performance when co-located with your site.

We hope this article provides you with some good ideas for what solution to select for your use case. For more ideas, have a look at our Site Search Buyer’s Guide or blog on Best Practices for Site Search.

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