Need advice about which tool to choose?Ask the StackShare community!
Elasticsearch vs Swagger UI: What are the differences?
Introduction
Elasticsearch and Swagger UI are both tools commonly used in website development, but they serve different purposes. Elasticsearch is a search engine that allows users to store, analyze, and search large volumes of data quickly and in real-time. Swagger UI, on the other hand, is a user interface that allows developers to document, explore, and interact with Application Programming Interfaces (APIs). Let's explore the key differences between Elasticsearch and Swagger UI in detail:
Data Storage and Retrieval: Elasticsearch is primarily used for data storage and retrieval, providing a distributed, flexible, and scalable search engine. It enables users to perform complex search operations on structured and unstructured data using various query types. On the other hand, Swagger UI does not store data but rather serves as a tool to visualize and interact with APIs. It provides a user-friendly interface to explore available API endpoints and make test requests.
Search Capabilities: Elasticsearch offers comprehensive search capabilities, including full-text search, fuzzy search, geo-search, and even relevance scoring. It supports advanced search features like aggregations, filtering, and sorting, making it suitable for building robust search functionalities. Swagger UI, on the other hand, does not have built-in search capabilities as it focuses primarily on API documentation and testing.
API Documentation vs. Search Engine: Swagger UI excels in API documentation and provides an interactive interface for developers to explore available endpoints, query parameters, request/response schemas, and example requests. It automatically generates documentation by analyzing the API's OpenAPI (formerly known as Swagger) specification. Elasticsearch, on the other hand, is not designed for API documentation but rather as a search engine that powers search functionalities for various applications.
Integration and Compatibility: Elasticsearch is commonly integrated into web development projects to power advanced search functionalities within applications. It offers compatibility with various programming languages, frameworks, and libraries, making it highly versatile. Swagger UI, on the other hand, integrates with APIs and can be used in conjunction with different backend frameworks and languages to provide interactive documentation and testing capabilities.
Real-time Data Updates: Elasticsearch is built for real-time data updates, allowing users to index and retrieve data in milliseconds. It provides powerful near real-time indexing capabilities, making it suitable for use cases where the data is frequently changing or requires immediate search updates. Swagger UI, on the other hand, does not handle real-time data updates, as it primarily focuses on API documentation and testing rather than data storage and retrieval.
Development vs. Deployment: Elasticsearch requires deployment and configuration as a separate service or cluster, usually hosted on dedicated hardware or cloud infrastructure. It requires additional setup to ensure high availability, durability, and scalability. On the contrary, Swagger UI is a library that can be embedded within an application or hosted as a standalone web page. It simplifies the development of API documentation but does not require extensive deployment and infrastructure management like Elasticsearch.
In summary, Elasticsearch is a powerful search engine designed for data storage, retrieval, and real-time search operations, while Swagger UI is a user interface for API documentation and testing. Elasticsearch provides advanced search features, while Swagger UI focuses on visualizing and exploring APIs.
Hey everybody! (1) I am developing an android application. I have data of around 3 million record (less than a TB). I want to save that data in the cloud. Which company provides the best cloud database services that would suit my scenario? It should be secured, long term useable, and provide better services. I decided to use Firebase Realtime database. Should I stick with Firebase or are there any other companies that provide a better service?
(2) I have the functionality of searching data in my app. Same data (less than a TB). Which search solution should I use in this case? I found Elasticsearch and Algolia search. It should be secure and fast. If any other company provides better services than these, please feel free to suggest them.
Thank you!
Hi Rana, good question! From my Firebase experience, 3 million records is not too big at all, as long as the cost is within reason for you. With Firebase you will be able to access the data from anywhere, including an android app, and implement fine-grained security with JSON rules. The real-time-ness works perfectly. As a fully managed database, Firebase really takes care of everything. The only thing to watch out for is if you need complex query patterns - Firestore (also in the Firebase family) can be a better fit there.
To answer question 2: the right answer will depend on what's most important to you. Algolia is like Firebase is that it is fully-managed, very easy to set up, and has great SDKs for Android. Algolia is really a full-stack search solution in this case, and it is easy to connect with your Firebase data. Bear in mind that Algolia does cost money, so you'll want to make sure the cost is okay for you, but you will save a lot of engineering time and never have to worry about scale. The search-as-you-type performance with Algolia is flawless, as that is a primary aspect of its design. Elasticsearch can store tons of data and has all the flexibility, is hosted for cheap by many cloud services, and has many users. If you haven't done a lot with search before, the learning curve is higher than Algolia for getting the results ranked properly, and there is another learning curve if you want to do the DevOps part yourself. Both are very good platforms for search, Algolia shines when buliding your app is the most important and you don't want to spend many engineering hours, Elasticsearch shines when you have a lot of data and don't mind learning how to run and optimize it.
Rana - we use Cloud Firestore at our startup. It handles many million records without any issues. It provides you the same set of features that the Firebase Realtime Database provides on top of the indexing and security trims. The only thing to watch out for is to make sure your Cloud Functions have proper exception handling and there are no infinite loop in the code. This will be too costly if not caught quickly.
For search; Algolia is a great option, but cost is a real consideration. Indexing large number of records can be cost prohibitive for most projects. Elasticsearch is a solid alternative, but requires a little additional work to configure and maintain if you want to self-host.
Hope this helps.
From a StackShare Community member: "I just started working for a start-up and we are in desperate need of better documentation for our API. Currently our API docs is in a README.md file. We are evaluating Postman and Swagger UI. Since there are many options and I was wondering what other StackSharers would recommend?"
I use Postman because of the ease of team-management, using workspaces and teams, runner, collections, environment variables, test-scripts (post execution), variable management (pre and post execution), folders (inside collections, for better management of APIs), newman, easy-ci-integration (and probably a few more things that I am not able to recall right now).
I use Swagger UI because it's an easy tool for end-consumers to visualize and test our APIs. It focuses on that ! And it's directly embedded and delivered with the APIs. Postman's built-in tools aren't bad, but their main focus isn't the documentation and also, they are hosted outside the project.
I recommend Postman because it's easy to use with history option. Also, it has very great features like runner, collections, test scripts runners, defining environment variables and simple exporting and importing data.
Pros of Elasticsearch
- Powerful api328
- Great search engine315
- Open source231
- Restful214
- Near real-time search200
- Free98
- Search everything85
- Easy to get started54
- Analytics45
- Distributed26
- Fast search6
- More than a search engine5
- Great docs4
- Awesome, great tool4
- Highly Available3
- Easy to scale3
- Potato2
- Document Store2
- Great customer support2
- Intuitive API2
- Nosql DB2
- Great piece of software2
- Reliable2
- Fast2
- Easy setup2
- Open1
- Easy to get hot data1
- Github1
- Elaticsearch1
- Actively developing1
- Responsive maintainers on GitHub1
- Ecosystem1
- Not stable1
- Scalability1
- Community0
Pros of Swagger UI
- Open Source49
- Can execute api calls from the documentation34
- Free to use29
- Customizable19
- Easy to implement in .Net14
- Mature, clean spec13
- API Visualization12
- Coverage9
- Scaffolding6
- Easy to use6
- Vibrant and active community5
- Elegant4
- Adopted by tm forum api3
- Clear for React2
- Api1
- Can deploy API to AWS API Gateway and AWS Lambda1
Sign up to add or upvote prosMake informed product decisions
Cons of Elasticsearch
- Resource hungry7
- Diffecult to get started6
- Expensive5
- Hard to keep stable at large scale4
Cons of Swagger UI
- Need to learn YAML and RAML3
- Documentation doesn't look that good2
- Doesn't generate code snippets in different languages1
- You don’t actually get in-line error highlighting1
- Does not support hypermedia1
Sign up to add or upvote consMake informed product decisions
What is Elasticsearch?
What is Swagger UI?
Need advice about which tool to choose?Ask the StackShare community!
What companies use Elasticsearch?
What companies use Swagger UI?
Sign up to get full access to all the companiesMake informed product decisions
What tools integrate with Swagger UI?
Sign up to get full access to all the tool integrationsMake informed product decisions
Blog Posts
+6
+17
+12
+4
+23+42+47
+39