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Score 9.2 out of 101
94 Ratings
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Score 8.8 out of 101

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Likelihood to Recommend

Algolia

If you have a dedicated developer who has the technical know-how to delve deep into Algolia's documentation to figure out what makes it tick, this is the product for you. Algolia's framework is extremely powerful, making search instantaneous and providing users with results at break-neck speeds. If all you need is great search, but you do not require a complex relevancy algorithm running it, Algolia will work well for you. The more complex your use case, the more expensive the product becomes.
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Elasticsearch

As the name implies, when you need to search thousands, millions, or billions text-based documents for keywords, Elasticsearch is great. The way it indexes and internally analyzes the content of your documents is very powerful. Assuming you have enough servers in your cluster with fast enough storage, querying those documents becomes a breeze.
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Pros

  • Algolia is lightning quick -- the fastest we found
  • Algolia has great tech support, tons of documentation, and many high quality ready-made plugins
  • Algolia allows for a high degree of customization
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  • Indexing. Elasticsearch can index thousands of documents per second.
  • Searching. Elasticsearch provides plenty of options for querying your data to get just the right information back.
  • Scalability. Elasticsearch has built-in features for replicating data and distributing load, so you don't have to invest a ton of time and effort into third-party or customized clustering and/or sharding solutions.
  • Backup. Elasticsearch has built-in options for backing up your data. If you're dealing with a large cluster, backing things up can get rather interesting from a storage perspective, but Elasticsearch has worked very well for us thus far.
  • Recovery. If part of your cluster goes offline, Elasticsearch generally does a decent job of staying online and recovering from the outage. Occasionally you'll lose nodes that house all copies of a given set of shards (which isn't fun), but Elasticsearch still handles that situation as well as can be expected.
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Cons

  • It is very expensive compared to elastic search which is relatively free.
  • Algolia does not support iPhone and Android, unlike Sharefile and Diqify
  • Algolia lacks the activity tracking and email integration
  • Algolia does not have any video tutorials.
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  • The online documentation is very difficult to use, both as a teaching tool and as a quick reference. The search syntax is arcane and not particularly "human friendly" and examples from the documentation are often insufficiently detailed to apply directly.
  • ElasticSearch is touted as "schemaless" when in fact mappings (aka schemas) are required for all but the most basic use cases.
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Likelihood to Renew

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Elasticsearch10.0
Based on 1 answer
We're pretty heavily invested in ElasticSearch at this point, and there aren't any obvious negatives that would make us reconsider this decision.
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Usability

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Elasticsearch10.0
Based on 1 answer
To get started with Elasticsearch, you don't have to get very involved in configuring what really is an incredibly complex system under the hood. You simply install the package, run the service, and you're immediately able to begin using it. You don't need to learn any sort of query language to add data to Elasticsearch or perform some basic searching.If you're used to any sort of RESTful API, getting started with Elasticsearch is a breeze. If you've never interacted with a RESTful API directly, the journey may be a little more bumpy. Overall, though, it's incredibly simple to use for what it's doing under the covers.
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Implementation

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Elasticsearch9.0
Based on 1 answer
Do not mix data and master roles. Dedicate at least 3 nodes just for Master
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Alternatives Considered

Algolia at first seemed and proved to be the fastest compared to the other search engines. It is very easy to implement. Also, it had a 24x7 support which proved to be very useful. It is also useful for all types of clients weather it be organizations or individuals. It can also handle typos. It also focuses on features like API and SSL Security. Also, it is designed to search records, not pages. These were some of the reasons we went ahead with Algolia.
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ElasticSearch was easier to scale and faster than Mongo.
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Return on Investment

  • Algolia is very fast but also very expensive. However, the size of our organization is very huge, so cost is not much of a problem.
  • Algolia does not support iPhone and Android. This is a major issue, which is why we were considering moving to swiftype.
  • Since it has integration issues, we could not fully leverage the software.
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  • (Negative) Expense: Just Time. Early on, I had issues getting it installed in an exotic distribution, so labor/hours invested.
  • (Positive) Configuration and Modularity: You don't *have* to implement a full ELK stack. In fact, you could just run one, two or three components. However, marrying up ES with something like Syslog-ng, you combine two very powerful, feature-rich software packages in their own right, into an amazingly powerful data collection and gathering tool.
  • (Positive) Shallow learning curve: if you can write your own Unix configuration files, you will be able to maintain and develop on Elasticsearch.
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Pricing Details

Algolia

General
Free Trial
Free/Freemium Version
Premium Consulting/Integration Services
Entry-level set up fee?
No
Additional Pricing Details

Elasticsearch

General
Free Trial
Free/Freemium Version
Premium Consulting/Integration Services
Entry-level set up fee?
No
Additional Pricing Details