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What are the best self-hosted search engines?
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Mar 6, 2023
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9
Options
Considered
Best self-hosted search engines
Price
Price
Last Updated
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Solr
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Mar 6, 2023
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Ambar
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May 7, 2021
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ElasticSearch
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Mar 27, 2021
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Typesense
0
Free
Jul 27, 2022
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Searx
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Aug 31, 2022
See Full List
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Solr
My Rec
ommendation
for
Solr
My Recommendation for
Solr
All
10
Pros
8
Cons
2
Top
Pro
•••
SpellChecker
Solr allows has the functionality to check and correct spelling mistakes in search queries. The three main implementations are: IndexBasedSpellChecker WordBreadkSolrSpellChecker DirectSolrSpellChecker
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Top
Con
•••
General missing features
Solr is currently missing the following general features: Per-doc/query analyzer chain Support for nested documents Support for multiple document types per schema Ability to modify document scores with custom scripts Equivalent to Elasticsearch's percolation
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Top
Pro
•••
Results grouping
Solr allows you to group search results. Results can be grouped by: Field Value Query Function Query You can also collapse multiple results with the same field value down to a single result.
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Top
Con
•••
Missing some useful features for cloud distribution
Solr is currently missing the following features that are useful when managing a distributed system: Automatic shard rebalancing Ability to re-locate shards and replicas on demand Ability to change the schema without restarting the server Ability to search across multiple indexes.
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Top
Pro
•••
Open source
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Top
Pro
•••
Decision tree faceting
Solr has a faceting feature called pivot facets or 'decision tree facets'. Pivot facets enable you to calculate facets inside a parents facet, for example pivoting on 'size' than 'color' returns 'color' facet counts for each 'size' facet
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Top
Pro
•••
Hosting support
The following services will host Solr for you. The great thing about these services is that they abstract away some of the difficulty of scaling Solr: WebSolr SolrHQ
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Top
Pro
•••
Customizablity
A key differentiator of Solr is the level of customizability the SearchComponent feature provides. SearchComponent provides the developer astonishing flexibility in the way search queries are assembled and executed. At the time of writing, there does not appear to be a ElasticSearch equivalent of SearchComponent. source Whilst ElasticSearch has a number of plugin-points there doesn't appear to be an equivalent of Solr's SearchComponent that enables you to modify the workflow of existing API endpoints.
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Top
Pro
•••
Local params
Solr has a great feature that enables you to use LocalParams to perform more advanced faceting. They provide a way to "localize" information about a specific argument that is being sent to Solr. In other words, LocalParams provide a way to add meta-data to certain argument types such as query strings. From the Solr Wiki: LocalParams are expressed as prefixes to arguments to be sent to Solr. For example: Assume we have the existing query parameter q=solr rocks We can prefix this query string with LocalParams to provide more information to the query parser, for example changing the default operator type to "AND" and the default field to "title" for the lucene query parser: q={!q.op=AND df=title}solr rocks
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Top
Pro
•••
Stats component
Solr allows to view average, standard deviation, maximum, minimum, sum of squares of a particular numeric field. It also allows faceting of that numeric field based on the value(s) of other fields.
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Recommend
9
--
Ambar
My Rec
ommendation
for
Ambar
My Recommendation for
Ambar
All
4
Pros
3
Cons
1
Top
Pro
•••
Very easy to use
Has a user-friendly web-based interface with real-time statistics, intuitive administration tools and a REST API.
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Top
Con
•••
Only works in Unix
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Top
Pro
•••
Supports instant search
Analyzes the language used to construct search queries for fuzzy querying, phrases and metadata search. This is all done almost instantaneously, no matter how many documents are indexed or how long the query itself is.
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Top
Pro
•••
Horizontally scalable
The database can be horizontally scaled to petabytes of data because of its powerful multi-source document collection and deduplication. Smart content retrieval and indexing for any file type also helps a lot with search speeds when you are dealing with a massive amount of data.
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Recommend
4
--
ElasticSearch
My Rec
ommendation
for
ElasticSearch
My Recommendation for
ElasticSearch
All
15
Pros
12
Cons
3
Top
Pro
•••
Aggregations
Another area where ElasticSearch shines is its aggregations features. Similarly to facets (now deprecated), aggregations allow calculating and summarizing data of a query as it happens. Aggregations brings the ability to be nested and is broadly categorized as metrics aggregations and bucket aggregations. "aggregations" : { "<aggregation_name>" : { "<aggregation_type>" : { <aggregation_body> }, ["aggregations" : { [<sub_aggregation>]* } ] } [,"<aggregation_name_2>" : { ... } ]* }
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Top
Con
•••
Some missing features
Elasticsearch is currently missing the following features: Results Grouping / Field Collapsing Autocomplete Spell Checker/Did you mean (Available as a third-party plugin) Decision Tree Faceting Query Elevation Hash-based deduplication.
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Top
Pro
•••
Structured search queries with JSON
Search can be executed either using a simple, Lucene-based query string or using an extensive JSON-based search query DSL. By structuring the query as a JSON object you can be very explicit and can dictate exactly what ElasticSeach will return. A very basic example of a JSON query is: curl -XGET 'http://localhost:9200/blog/_search?pretty=true' -d ' { "query" : { "range" : { "postDate" : { "from" : "2011-12-10", "to" : "2011-12-12" } } } }'
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Top
Con
•••
Poor documentation
As a relatively new project, the documentation for ElasticSearch still leaves much to be desired. Documentation assumes that the user at least has familiarity with similar document stores, and is largely oriented toward those already familiar with other search solutions, such as Solr. Errors, while often quite simple to resolve, can be difficult to troubleshoot, as they are often insufficiently descriptive and missing from documentation. New users should be sure to check the tutorials section on elasticsearch.org for supplementary information lacking from the guide, such as more detailed installation instructions.
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Top
Pro
•••
Handles nested documents
ElasticSearch natively handles a nested document structure. ElasticSearch will index nested documents as a separate indexes and are stored in such a way that allow quick join operations to access them. Nested documents require a nested query to access so that don't clutter results from standard queries.
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Top
Con
•••
Prone to 'Split Brain' Situations
The Sematex blog explains a problem with the way Elasticsearch handles its clusters, called the 'Split Brain Situation': Imagine a situation, where you cluster is divided into half, so half of your nodes don’t see the other half, for example because of the network failure. In such cases Elasticsearch will try to elect a new master in the cluster part that doesn’t have one and this will lead to creation of two independent clusters running at the same time. This can be limited with a small degree of configuration, but it can still happen. Users have already run into this problem in production and ElasticSearch host Bonsai also have had issues with this problem as recently as March 2012.
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Top
Pro
•••
Percolator (prospective search)
Essentially a reverse search. The percolator allows you to register queries against an index, and then send percolate requests which include a doc, and getting back the queries that match on that doc out of the set of registered queries. Not possible in Solr out of the box.
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Top
Pro
•••
Open source
It's free and Open Source so you can host it yourself for free or even tweak it.
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Top
Pro
•••
Allows multiple types of documents per index
Another useful and unique feature to Elasticsearch is the ability to have multiple types of documents in a single index. You can then facet, query or filter against all document types or a single type.
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Top
Pro
•••
Designed to be distributed
The one area where Elasticsearch shines is distributed search. It was built from the ground up to be suitable for high-scale 'cloud' applications. There are many features Elasticsearch has as a result of being designed to be distributed that aren't currently available in Solr, such as: Shards and replicas can to moved to any node in the cluster on demand. With a simple API call you can increase and decrease the number of replicas without the need of shutting down nodes or creating new nodes. Manipulate shard placement with the cluster reroute API on a live cluster. Search across multiple indexes. Change the schema without restarting the server. Automatic shard rebalancing Elasticsearch also has a module called Gateway, that in the case of the whole cluster crashing or being taken down will enable you to easily restore the latest state of the cluster when it gets back up. Services such as Bonsai further simplify scaling Elasticsearch by hosting and scaling the search servers for you, making it nearly as easy to get started as CloudSearch or Searchify. Elasticsearch was also specifically designed to run well and be relatively easy to setup on EC2.
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Top
Pro
•••
Rapid feature development
Another thing to keep in mind when choosing a search solution is the development momentum. ElasticSearch has quickly caught up to the competition and most of the currently missing features are due to be released in upcoming versions.
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Top
Pro
•••
RESTful JSON API for configuration/management
Elasticsearch has a REST API for management and configuration. The following are the main features of this API: Index Management: Create, delete, close and open indices by running a simple HTTP command. Increase and decrease the number of replicas without the need of shutting down nodes or creating new nodes. Manipulate shard placement with the cluster reroute API. Move shards between nodes, we can cancel shard allocation process and we can also force shard allocation – everything on a live cluster. Check index and types existence Configuration: Majority of configuration files can be modified dynamically. Update Mappings Define, retrieve and manage warning queries Shut down the entire cluster or a specific node Clear caches on the index level This is all done over JSON, making it a lot more structured then the methods used in Solr.
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Top
Pro
•••
Pluggable Field Types
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Top
Pro
•••
Schemaless
Elasticsearch makes it easy to get started by not requiring you to define a schema before sending documents to be indexed. Elasticsearch will automatically guess field types for you, which although will not be as accurate as creating the mappings manually, is usually pretty accurate. Elasticsearch also lets you manually define the mappings (index structure) before creating the index. One cool feature is if you miss a field or add a new field without defining the mapping, Elasticsearch will try to guess the Type for you.
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Top
Pro
•••
Easy to work with
Elasticsearch gained its popularity amongst developers by being enjoyable to use. A simple feature comparison against it's competition doesn't convey the significant advantages of just how easy it is to work with. This is due to multiple design choices such as the use of JSON for the API and queries.
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Recommend
5
--
Typesense
My Rec
ommendation
for
Typesense
My Recommendation for
Typesense
All
1
Specs
Specs
Price:
Free
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0
Recommend
3
--
Searx
My Rec
ommendation
for
Searx
My Recommendation for
Searx
All
7
Pros
6
Cons
1
Top
Pro
•••
Extremely customisable
Since you have access to all the .yaml files, you can easily modify it to your needs.
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Top
Con
•••
Not very mobile friendly
Needs WSL2 for windows, and works natively on macOS and Linux But no support for Android or iOS
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Top
Pro
•••
Can add many search engines
Have a vast choice for choosing search engines
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Top
Pro
•••
Can use a proxy
Using a proxy called Morty hides the IP address of the user
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Top
Pro
•••
Most Private Search engine
Since it can be hosted on your own server/ computer, it is very private, nothing leaves your computer. No cookies or ads too
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Top
Pro
•••
Very fast
Since it is a Python program with a web interface, it's very very fast even on a poor internet connection
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Top
Pro
•••
Supports instant answers
Uses Google and Bing, and hence has the 'quick answers' feature of both the search engines.
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Recommend
4
3
--
Algolia
My Rec
ommendation
for
Algolia
My Recommendation for
Algolia
All
3
Experiences
1
Cons
2
Top
Con
•••
Commercial
There is a Free tier limited to 10k records that can only do 100k operations.
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FunnyInuus's Experience
Ithellam sahikalla
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Top
Con
•••
ithellam sahikkala
worse than searX
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Recommend
4
1
--
Appbase.io
My Rec
ommendation
for
Appbase.io
My Recommendation for
Appbase.io
All
6
Pros
6
Top
Pro
•••
Flexible deployment options
Run as a Fully Managed service, with an existing Elasticsearch cluster or self-host
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Top
Pro
•••
UI components and kits to build search faster
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Top
Pro
•••
Supports geolocation, query rules, synonyms, typos
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Top
Pro
•••
Built-in access control
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Top
Pro
•••
Out-of-the-box search analytics
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Top
Pro
•••
Search relevance control plane
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here
Recommend
1
--
Yacy
My Rec
ommendation
for
Yacy
My Recommendation for
Yacy
Hide
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here
Recommend
--
FTServer
My Rec
ommendation
for
FTServer
My Recommendation for
FTServer
All
3
Experiences
1
Pros
2
Top
Pro
•••
Android APK support
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SmartMinawara's Experience
High performance Search engine, has Java version, C# version, Android version, download and run, no setup.
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Top
Pro
•••
Open Source
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Recommend
1
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