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Amazon Elasticsearch Service vs Bonsai: What are the differences?
Introduction: Amazon Elasticsearch Service and Bonsai are two popular options for managing Elasticsearch clusters for search and analytics purposes. While they both offer similar functionality, there are key differences between the two services.
Hosting Environment: Amazon Elasticsearch Service is a fully managed service provided by Amazon Web Services (AWS), allowing users to easily spin up and manage Elasticsearch clusters within the AWS cloud environment. On the other hand, Bonsai is a third-party service provider that hosts Elasticsearch clusters in various cloud providers such as AWS, Google Cloud, and Azure. This difference in hosting environments can impact factors such as performance, integration, and support options.
Scalability Options: Amazon Elasticsearch Service offers seamless scalability options, allowing users to easily scale their clusters up or down based on demand. It also provides integration with other AWS services for automated scaling. In contrast, Bonsai's scalability options might be limited depending on the cloud provider chosen for hosting. Users may need to manage scaling manually or rely on the capabilities provided by the specific cloud provider.
Cost Structure: The cost structure of Amazon Elasticsearch Service is typically based on a pay-as-you-go model, with pricing determined by factors such as instance type, storage, and data transfer. Bonsai, on the other hand, offers more flexibility in pricing options, including flat-rate plans and volume-based pricing. Depending on the specific needs and budget of the user, one service may be more cost-effective than the other.
Support and Maintenance: Amazon Elasticsearch Service comes with the backing of AWS support, offering various tiers of support options including 24/7 technical support. Bonsai also provides support but the level and responsiveness may vary depending on the plan chosen. Users looking for a robust support system may find Amazon Elasticsearch Service more suitable for their needs.
Customization and Control: While both services offer management of Elasticsearch clusters, Amazon Elasticsearch Service may provide more limitations in terms of customization and control compared to Bonsai. Bonsai allows for more granular control over configuration settings, plugins, and Elasticsearch versions, giving users greater flexibility in tailoring their clusters to specific requirements.
Data Residency and Compliance: Amazon Elasticsearch Service allows users to specify the region in which their data is stored, ensuring compliance with data residency regulations and requirements. Bonsai, being a third-party provider, may have limitations in terms of data residency options depending on the cloud provider chosen for hosting. Users with strict data residency and compliance needs should consider these differences when selecting a service.
In Summary, Amazon Elasticsearch Service offers a fully managed Elasticsearch solution within the AWS cloud environment, providing seamless scalability, robust support options, and data residency compliance. Bonsai, on the other hand, is a third-party service that offers more pricing flexibility, customization control, and scalability limitations depending on the cloud provider chosen.
Hi, community, I'm planning to build a web service that will perform a text search in a data set off less than 3k well-structured JSON objects containing config data. I'm expecting no more than 20 MB of data. The general traits I need for this search are: - Typo tolerant (fuzzy query), so it has to match the entries even though the query does not match 100% with a word on that JSON - Allow a strict match mode - Perform the search through all the JSON values (it can reach 6 nesting levels) - Ignore all Keys of the JSON; I'm interested only in the values.
The only thing I'm researching at the moment is Elasticsearch, and since the rest of the stack is on AWS the Amazon ElasticSearch is my favorite candidate so far. Although, the only knowledge I have on it was fetched from some articles and Q&A that I read here and there. Is ElasticSearch a good path for this project? I'm also considering Amazon DynamoDB (which I also don't know of), but it does not look to cover the requirements of fuzzy-search and ignore the JSON properties. Thank you in advance for your precious advice!
I think elasticsearch should be a great fit for that use case. Using the AWS version will make your life easier. With such a small dataset you may also be able to use an in process library for searching and possibly remove the overhead of using a database. I don’t if it fits the bill, but you may also want to look into lucene.
I can tell you that Dynamo DB is definitely not a good fit for your use case. There is no fuzzy matching feature and you would need to have an index for each field you want to search or convert your data into a more searchable format for storing in Dynamo, which is something a full text search tool like elasticsearch is going to do for you.
Maybe you can do it with storing on S3, and query via Amazon Athena en AWS Glue. Don't know about the performance though. Fuzzy search could otherwise be done with storing a soundex value of the fields you want to search on in a MongoDB. In DynamoDB you would need indexes on every searchable field if you want it to be efficient.
The Amazon Elastic Search service will certainly help you do most of the heavy lifting and you won't have to maintain any of the underlying infrastructure. However, elastic search isn't trivial in nature. Typically, this will mean several days worth of work.
Over time and projects, I've over the years leveraged another solution called Algolia Search. Algolia is a fully managed, search as a service solution, which also has SDKs available for most common languages, will answer your fuzzy search requirements, and also cut down implementation and maintenance costs significantly. You should be able to get a solution up and running within a couple of minutes to an hour.
The new pricing model Algolia introduced really sealed the deal for us on this one - much closer to pay-as-you-go. And didn't want to spend time learning more about hosting/optimizing Elasticsearch when that isn't our core business problem - would much rather pay others to solve that problem for us.
Pros of Amazon Elasticsearch Service
- Easy setup, monitoring and scaling10
- Kibana7
- Document-oriented7
Pros of Bonsai
- Free tier2
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