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Amazon Textract VS MongoDB

Compare Amazon Textract VS MongoDB and see what are their differences

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Amazon Textract logo Amazon Textract

Easily extract text and data from virtually any document using Amazon Textract. Textract goes beyond simple optical character recognition (OCR) to also identify the contents of fields in forms and information stored in tables.

MongoDB logo MongoDB

MongoDB (from "humongous") is a scalable, high-performance NoSQL database.
  • Amazon Textract Landing page
    Landing page //
    2023-04-13
  • MongoDB Landing page
    Landing page //
    2023-10-21

Amazon Textract features and specs

  • Accurate Data Extraction
    Amazon Textract uses machine learning and OCR technologies to provide high accuracy in extracting text and structured data from various document formats.
  • Supports Multiple Formats
    Textract can handle different document types, including PDFs, scanned images, and more, making it versatile for various use cases.
  • Ease of Integration
    Amazon Textract offers APIs that are easy to integrate with other AWS services and external applications, enhancing its usability.
  • Security and Compliance
    Being part of AWS, Textract adheres to robust security and compliance standards, ensuring data protection and privacy.
  • Scalability
    Textract is highly scalable and can process large volumes of documents efficiently, catering to both small businesses and large enterprises.

Possible disadvantages of Amazon Textract

  • Cost
    Amazon Textract can become expensive as the volume of document processing increases, which may be a concern for small businesses with limited budgets.
  • Complexity of Setup
    Though integration is straightforward, initial setup and configuration can be complex, requiring familiarity with AWS services and APIs.
  • Limited Advanced Features
    Textract may lack some advanced features and customization options that are available in more specialized OCR alternatives.
  • Dependency on AWS Ecosystem
    Exclusive reliance on AWS services can be a drawback for organizations that utilize a multi-cloud or hybrid cloud strategy.
  • Quality of Original Documents
    Textract’s accuracy largely depends on the quality of the original documents. Poor quality scans or heavily damaged documents may yield less accurate results.

MongoDB features and specs

  • Scalability
    MongoDB offers horizontal scaling through sharding, allowing it to handle large volumes of data and enabling distributed computing.
  • Flexible Schema
    It allows for a flexible schema design using BSON (Binary JSON), making it easier to iterate and change application data models.
  • High Performance
    MongoDB is optimized for read and write throughput, making it suitable for real-time applications.
  • Rich Query Language
    Supports a rich and expressive query language that allows for efficient querying and analytics.
  • Built-in Replication
    Provides robust replication mechanisms for high availability and redundancy.
  • Geospatial Indexing
    Offers powerful geospatial indexing capabilities, useful for location-based applications.
  • Aggregation Framework
    Enables complex data manipulations and transformations using the aggregation pipeline framework.
  • Cross-Platform
    Works on multiple operating systems, enhancing its versatility and deployment options.

Possible disadvantages of MongoDB

  • Memory Usage
    MongoDB can consume a large amount of memory due to its use of memory-mapped files, which may be a concern for some applications.
  • Complex Transactions
    While MongoDB supports ACID transactions, they can be more complex to implement and less efficient compared to traditional relational databases.
  • Data Redundancy
    The flexible schema design can lead to data redundancy and increased storage costs if not managed carefully.
  • Limited Joins
    Joins are supported but can be less efficient and more limited compared to relational databases, affecting complex relational data querying.
  • Indexing Overhead
    Extensive indexing can introduce overhead and impact performance, especially during write operations.
  • Learning Curve
    Requires a different mindset and understanding compared to traditional relational databases, which can present a learning curve for new users.
  • Lacks Mature Analytical Tools
    The ecosystem for analytical tools around MongoDB is not as mature as those for traditional relational databases, which might limit advanced analytics capabilities.
  • Cost
    The cost of using MongoDB's cloud services (MongoDB Atlas) can be high, especially for large-scale deployments.

Analysis of Amazon Textract

Overall verdict

  • Yes, Amazon Textract is generally considered a good service for its intended purposes.

Why this product is good

  • Amazon Textract is effective because it uses advanced machine learning techniques to automatically extract text, handwriting, and data from scanned documents. It is highly accurate, scalable, and integrates well with other AWS services, which makes it convenient for businesses looking to automate document processing.

Recommended for

  • Organizations looking to automate data extraction from large volumes of documents.
  • Companies needing to process forms and tables quickly and accurately.
  • Developers looking for a cloud-based OCR service that integrates with other AWS solutions.
  • Industries such as finance, healthcare, and legal, where document digitization is essential.

Analysis of MongoDB

Overall verdict

  • MongoDB is generally regarded as a good database solution for applications needing flexibility, scalability, and fast development times. However, it may not be the best choice for applications requiring complex transactions or where ACID compliance is critical, as it originally prioritized availability over consistency. Recent improvements, including multi-document transactions, have addressed some concerns, making it more versatile.

Why this product is good

  • MongoDB is considered a good choice for certain types of applications due to its flexible schema design, scalability, horizontal scaling capabilities, and ease of use for developers who require rapid development cycles. It supports a wide range of data types and allows for full-text search, geospatial queries, and aggregation operations. MongoDB's document-oriented storage makes it well-suited for handling large volumes of unstructured data. Its robust ecosystem, including Atlas for cloud deployments, adds to its appeal by offering automated scaling, backups, and distributed architecture.

Recommended for

  • Applications requiring high scalability and performance with unstructured data
  • Real-time analytics and big data applications
  • Web and mobile applications needing rapid development and flexible data models
  • Projects that benefit from cloud-native solutions with managed services

Amazon Textract videos

+ Add

Amazon Textract: First Look

More videos:

  • Review - AWS re:Invent 2018 – Announcing Amazon Textract
  • Review - Introducing Amazon Textract: Now in Preview

MongoDB videos

+ Add

MySQL vs MongoDB

More videos:

  • Review - The Good and Bad of MongoDB
  • Review - what is mongoDB

Category Popularity

0-100% (relative to Amazon Textract and MongoDB)

Amazon Textract

MongoDB

OCR
100 100%
OCR
0% 0
Databases
0 0%
Databases
100% 100
OCR API
100 100%
OCR API
0% 0
NoSQL Databases
0 0%
NoSQL Databases
100% 100

User comments

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Reviews

These are some of the external sources and on-site user reviews we've used to compare Amazon Textract and MongoDB

Amazon Textract Reviews

2019 Examples to Compare OCR Services: Amazon Textract/Rekognition vs Google Vision vs Microsoft Cognitive Services
Pricing: Amazon Rekognition, Amazon Textract, Google, Microsoft. We don't really care which one you use, but Microsoft did best by our sample data. Textract was a very close second if you only need its headline feature: extracting text from digital documents. If someone wants to email bill -at- amplenote.com with comparable data for other images/services, I can try to...
Source: www.amplenote.com

MongoDB Reviews

10 Top Firebase Alternatives to Ignite Your Development in 2024
MongoDB’s superpower lies in its flexibility. Its document-based model lets you store data in a free-form, schema-less way, making it adaptable to evolving application needs. Need to add a new field or change the structure of your data? No problem, MongoDB handles it with ease.
Source: genezio.com
Top 7 Firebase Alternatives for App Development in 2024
MongoDB Realm provides a robust alternative to Firebase, especially for apps requiring a flexible data model. Key features include:
Source: signoz.io
Announcing FerretDB 1.0 GA - a truly Open Source MongoDB alternative
MongoDB is no longer open source. We want to bring MongoDB database workloads back to its open source roots. We are enabling PostgreSQL and other database backends to run MongoDB workloads, retaining the opportunities provided by the existing ecosystem around MongoDB.
Source: blog.ferretdb.io
16 Top Big Data Analytics Tools You Should Know About
The database added a new feature to its list of attributes called MongoDB Atlas. It is a global cloud database technology that allows to deploy a fully managed MongoDB across AWS, Google Cloud, and Azure with its built-in automation for resource, workload optimization and to reduce the time required to handle the database.
Source: www.analytixlabs.co.in
9 Best MongoDB alternatives in 2019
MongoDB is an open source NoSQL DBMS which uses a document-oriented database model. It supports various forms of data. However, in MongoDB data consumption is high due to de-normalization.
Source: www.guru99.com

Social recommendations and mentions

Based on our record, Amazon Textract should be more popular than MongoDB. It has been mentiond 37 times since March 2021. We are tracking product recommendations and mentions on various public social media platforms and blogs. They can help you identify which product is more popular and what people think of it.

Amazon Textract mentions (37)

  • From PartyRock to Bedrock: AI-Powered Automation at Work
    We were a little concerned that working with documents and Bedrock was going to mean a bunch of effort by using Texttract. I was glad we were proven wrong. I was able to build a quick proof of concept using the Bedrock API in 10 - 15 minutes. - Source: dev.to / 4 months ago
  • Mastering Text Extraction from Multi-Page PDFs Using OCR API: A Step-by-Step Guide
    Amazon Textract is an OCR service provided by Amazon Web Services (AWS), specifically designed to extract text and data from scanned documents and images. It not only recognizes text but also comprehends the document's structure, including tables and forms. This capability makes it especially valuable for applications requiring detailed data extraction, such as invoice processing and form digitization. - Source: dev.to / 11 months ago
  • Ask HN: How to OCR a PDF and preserve whitespace?
    Did you try textract? https://aws.amazon.com/textract/ In my experience it works amazingly well with columns / tabulated content. - Source: Hacker News / 12 months ago
  • Classifying and Extracting Data using Amazon Textract
    Amazon Textract has an Analyze Lending API for evaluating and categorizing the documents contained in mortgage loan application packages, as well as extracting the data they contain. The new API can assist in processing applications quicker and with minimal errors, therefore improving the end-customer experience and lowering operational costs. - Source: dev.to / over 1 year ago
  • Ask HN: OCR for 100 year old (German) handwritten cursive script?
    You could try something like https://aws.amazon.com/textract/ or https://cloud.google.com/vision/docs/handwriting. Both have support for modern handwriting. I don't know if it will work with a script written a century ago though. - Source: Hacker News / over 1 year ago
View more

MongoDB mentions (18)

  • Creating AI Memories using Rig & MongoDB
    In this article, we’ll build a CLI tool using the Rig AI framework and MongoDB for retrieval-augmented generation (RAG). This tool will store summarized conversations in a database and retrieve them when needed, enabling the AI to maintain context over time. - Source: dev.to / 2 months ago
  • The Adventures of Blink S2e2: Database, Contained
    Have a Mongo database holding the various phrases we're going to use and potentially configuration data for the frontend as well. - Source: dev.to / 9 months ago
  • Introducing Perseid: The Product-oriented JS framework
    It's also worth mentioning that Perseid provides out-of-the-box support for React, VueJS, Svelte, MongoDB, MySQL, PostgreSQL, Express and Fastify. - Source: dev.to / 9 months ago
  • DocumentDB Elastic Cluster Pricing
    Does anyone know if the most basic Elastic Cluster instance of DocumentDB carries any monthly fixed cost or is it just on-demand cost? Another words if I run like 10,000 queries against the DB per month, what kind of bill would I expect? This is for a super small app. I am currently using mongodb free tier , but want to migrate everything to AWS. Can't seem to find a straight answer to the pricing question. Source: over 2 years ago
  • I wrote some scripts for converting the UTZOO Usenet archive to a Mongo Database
    You can use either MongoDB.com's dashboard (if you host a remote database) or Mongo Compass to run queries on the data or you can modify the express middleware with your own queries. I'm still working on the API, so it's not very robust yet. I will update this when it is. Source: over 2 years ago
View more

What are some alternatives?

When comparing Amazon Textract and MongoDB, you can also consider the following products

DocParser - Extract data from PDF files & automate your workflow with our reliable document parsing software. Convert PDF files to Excel, JSON or update apps with webhooks.

Redis - Redis is an open source in-memory data structure project implementing a distributed, in-memory key-value database with optional durability.

Nanonets OCR - Intelligent text extraction using OCR and deep learning

PostgreSQL - PostgreSQL is a powerful, open source object-relational database system.

Pen to Print - Pen to Print: Convert handwriting to text created and published by Serendi LTD.

MySQL - The world's most popular open source database

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