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  5. Algorithms.io vs Elasticsearch vs LogRocket

Algorithms.io vs Elasticsearch vs LogRocket

OverviewDecisionsComparisonAlternatives

Overview

Algorithms.io
Algorithms.io
Stacks48
Followers77
Votes0
Elasticsearch
Elasticsearch
Stacks35.5K
Followers27.1K
Votes1.6K
LogRocket
LogRocket
Stacks277
Followers278
Votes137

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Advice on Algorithms.io, Elasticsearch, LogRocket

Rana Usman
Rana Usman

Chief Technology Officer at TechAvanza

Jun 4, 2020

Needs adviceonFirebaseFirebaseElasticsearchElasticsearchAlgoliaAlgolia

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!

408k views408k
Comments
André
André

Nov 20, 2020

Needs adviceonElasticsearchElasticsearchAmazon DynamoDBAmazon DynamoDB

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!

60.3k views60.3k
Comments

Detailed Comparison

Algorithms.io
Algorithms.io
Elasticsearch
Elasticsearch
LogRocket
LogRocket

Build And Run Predictive Applications For Streaming Data From Applications, Devices, Machines and Wearables

Elasticsearch is a distributed, RESTful search and analytics engine capable of storing data and searching it in near real time. Elasticsearch, Kibana, Beats and Logstash are the Elastic Stack (sometimes called the ELK Stack).

LogRocket combines session replay, performance monitoring, and product analytics – empowering software teams to create the ideal product experience.

Classification & Anomaly Detection- With our machine learning algorithms and your time series data, we can get up to 99% prediction accuracy on the state of the sensor. Algorithms include neural network, random forest, support vector machine and others.;Streaming Data Infrastructure- We provide the infrastructure for your streaming data as a service including a highly scalable time-series database and analytics capabilities.;Analytics Across All Your Devices- Capture and aggregate data from all of your devices to perform analytics across the entire dataset.;Random Forest, SVM, Decision Tree, Node.js, Streaming Data
Distributed and Highly Available Search Engine;Multi Tenant with Multi Types;Various set of APIs including RESTful;Clients available in many languages including Java, Python, .NET, C#, Groovy, and more;Document oriented;Reliable, Asynchronous Write Behind for long term persistency;(Near) Real Time Search;Built on top of Apache Lucene;Per operation consistency;Inverted indices with finite state transducers for full-text querying;BKD trees for storing numeric and geo data;Column store for analytics;Compatible with Hadoop using the ES-Hadoop connector;Open Source under Apache 2 and Elastic License
Session replay; Inspect actions and state at any point in time; Network activity; Inspect console logs and JavaScript errors
Statistics
Stacks
48
Stacks
35.5K
Stacks
277
Followers
77
Followers
27.1K
Followers
278
Votes
0
Votes
1.6K
Votes
137
Pros & Cons
No community feedback yet
Pros
  • 329
    Powerful api
  • 315
    Great search engine
  • 231
    Open source
  • 214
    Restful
  • 200
    Near real-time search
Cons
  • 7
    Resource hungry
  • 6
    Diffecult to get started
  • 5
    Expensive
  • 4
    Hard to keep stable at large scale
Pros
  • 21
    See a video of user using your website
  • 20
    See full user sessions
  • 18
    Detect user frustration
  • 18
    Console, network, and error logging
  • 18
    See why users ask for support
Integrations
No integrations available
Kibana
Kibana
Beats
Beats
Logstash
Logstash
Jira
Jira
Sentry
Sentry
Intercom
Intercom
Trello
Trello
Mixpanel
Mixpanel
GitHub
GitHub
Segment
Segment
Bugsnag
Bugsnag
Rollbar
Rollbar
Errorception
Errorception

What are some alternatives to Algorithms.io, Elasticsearch, LogRocket?

Algolia

Algolia

Our mission is to make you a search expert. Push data to our API to make it searchable in real time. Build your dream front end with one of our web or mobile UI libraries. Tune relevance and get analytics right from your dashboard.

Typesense

Typesense

It is an open source, typo tolerant search engine that delivers fast and relevant results out-of-the-box. has been built from scratch to offer a delightful, out-of-the-box search experience. From instant search to autosuggest, to faceted search, it has got you covered.

FullStory

FullStory

FullStory’s unmatched analytics engine automatically indexes every digital interaction with your site or app and empowers teams to measure, validate, and act on each experience at scale.

Amazon CloudSearch

Amazon CloudSearch

Amazon CloudSearch enables you to search large collections of data such as web pages, document files, forum posts, or product information. With a few clicks in the AWS Management Console, you can create a search domain, upload the data you want to make searchable to Amazon CloudSearch, and the search service automatically provisions the required technology resources and deploys a highly tuned search index.

Amazon Elasticsearch Service

Amazon Elasticsearch Service

Amazon Elasticsearch Service is a fully managed service that makes it easy for you to deploy, secure, and operate Elasticsearch at scale with zero down time.

Manticore Search

Manticore Search

It is a full-text search engine written in C++ and a fork of Sphinx Search. It's designed to be simple to use, light and fast, while allowing advanced full-text searching. Connectivity is provided via a MySQL compatible protocol or HTTP, making it easy to integrate.

NanoNets

NanoNets

Build a custom machine learning model without expertise or large amount of data. Just go to nanonets, upload images, wait for few minutes and integrate nanonets API to your application.

Azure Search

Azure Search

Azure Search makes it easy to add powerful and sophisticated search capabilities to your website or application. Quickly and easily tune search results and construct rich, fine-tuned ranking models to tie search results to business goals. Reliable throughput and storage provide fast search indexing and querying to support time-sensitive search scenarios.

Swiftype

Swiftype

Swiftype is the easiest way to add great search to your website or mobile application.

MeiliSearch

MeiliSearch

It is a powerful, fast, open-source, easy to use, and deploy search engine. The search and indexation are fully customizable and handles features like typo-tolerance, filters, and synonyms.

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