
Realm.io
ObjectBox
Microsoft SQL Server Compact
CompactView
UnQLite
Clustrix
Microsoft SQL Server
VoltDB
DocParser
Nanonets
Parseur.com
Rossum
Docsumo
DocuClipper
FlexiCapture
Parsio.io
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Based on our record, Realm.io should be more popular than DocParser. It has been mentiond 25 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.
From the team at MongoDB comes Realm, a mobile database that runs directly inside phones, tablets, or wearables. It's built for mobile, and designed for offline use. The latest release comes with built-in Swift 6 language mode, and Xcode 16 support. Some breaking changes include removal of Atlas App Services and Atlas Device Sync functionality, Strings and Data now considered different types and thus queries won't... - Source: dev.to / almost 2 years ago
Looks really cool, I like to make very minimalistic dependency choices for the web apps I work on. Web Components look interesting and it's great to see frameworks that build upon it and provide features that are currently missing from it. When I landed on the page I remembered another Realm framework I used a lot long time ago. https://realm.io has the same name and the logo looks very similar too. Not sure if... - Source: Hacker News / almost 3 years ago
Realm is a fast, scalable alternative to SQLite with mobile to cloud data sync that makes building real-time, reactive mobile apps easy. - Source: dev.to / about 3 years ago
I would focus on Kotlin instead of Java, there's really no point in sticking to Java at this point. And when it comes to databases, some local ones that are pretty easy to get into are Realm and ObjectBox, SQLite can definitely be a bit overwhelming at the beginning. Source: over 3 years ago
Just to add to this, there's also Realm and ObjectBox as alternatives. Source: over 3 years ago
You could try an online service like https://extract-io.web.app/ or https://docparser.com/. Source: about 3 years ago
DocParser: DocParser simplifies the extraction of structured data from various file formats, such as PDFs and scanned documents, directly into Google Sheets. By automating this process, DocParser saves valuable time and effort otherwise spent on manual data entry. Link to DocParser. Source: over 3 years ago
There are several tools available today that can help you extract tables from PDF files (such as Tabula), or even parse PDFs into structured JSON using AI (like Parsio -> I'm the founder) or without AI (like Docparser). Source: over 3 years ago
Thank you for sharing those! I didn't know them I've only checked this one https://docparser.com/ and I think my solution could be better because it will be easier for the user. Source: over 3 years ago
As previously suggested, if the layout of your PDFs never changes (consistent column widths in tables and placement), you can use a zonal PDF parser like DocParser. Alternatively, an AI-powered parser may be a better choice. Source: over 3 years ago
ObjectBox - ObjectBox empower edge computing with an edge device database and synchronization solution for Mobile & IoT. Store and sync data from edge to cloud.
Nanonets - Worlds best image recognition, object detection and OCR APIs. NanoNets’ platform makes it straightforward and fast to create highly accurate Deep Learning models.
Microsoft SQL Server Compact - Bring Microsoft SQL Server 2017 to the platform of your choice. Use SQL Server 2017 on Windows, Linux, and Docker containers.
Parseur.com - Automate text extraction from emails and PDFs by using our powerful email and document parser.
CompactView - Viewer for Microsoft® SQL Server® CE database files (sdf)
Rossum - Rossum is AI-powered, cloud-based invoice data capture service that speeds up invoice processing 6x, with up to 98% accuracy. It can be easily customized, integrated and scaled according to your company needs.