The use of QDA software in social science research is so common that many people tend to see QDA software as a tool primarily for social science research. However, applications like MAXQDA are invaluable productivity tools for research analysts in industry or government as well.
Remarkably scalable, MAXQDA employs a database architecture that can handle research projects ranging in size from several dozen pages to tens of thousands of pages. Many projects today involve identifying connections found among information stored in PDF, Powerpoint presentations, Word documents, photos, videos, and audio recordings. MAXQDA allows users to code relevant sections of each document, identify interrelationships among documents, build relationships among diverse sets of documents and identify thematic trends.
MAXQDA features a simple 4 pane interface that makes it easy to use. The Document System- is where you place documents (text, images, video, or sound files) you want to analyse. The Document Browser is where you view the content of the document. The Coding System shows the various codes that you create and assign to documents. The Retrieved Segments Pane shows search results.
Based on our record, Apache Cassandra seems to be more popular. It has been mentiond 41 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.
Distributed storage Distributed storage systems like Cassandra, DynamoDB, and Voldemort also use consistent hashing. In these systems, data is partitioned across many servers. Consistent hashing is used to map data to the servers that store the data. When new servers are added or removed, consistent hashing minimizes the amount of data that needs to be remapped to different servers. - Source: dev.to / 9 days ago
On the other hand, NoSQL databases are non-relational databases. They store data in flexible, JSON-like documents, key-value pairs, or wide-column stores. Examples include MongoDB, Couchbase, and Cassandra. - Source: dev.to / about 1 month ago
HBase and Cassandra: Both cater to non-structured Big Data. Cassandra is geared towards scenarios requiring high availability with eventual consistency, while HBase offers strong consistency and is better suited for read-heavy applications where data consistency is paramount. - Source: dev.to / 3 months ago
Dear r/python, we are happy to present you with our first open-source project. We have managed to implement a new driver for Python that works with Apache Cassandra, ScyllaDB and AWS Keyspaces. Source: 8 months ago
NoSQL is a term that we have become very familiar with in recent times and it is used to describe a set of databases that don't make use of SQL when writing & composing queries. There are loads of different types of NoSQL databases ranging from key-value databases like the Reddis to document-oriented databases like MongoDB and Firestore to graph databases like Neo4J to multi-paradigm databases like FaunaDB and... - Source: dev.to / 9 months ago
MongoDB - MongoDB (from "humongous") is a scalable, high-performance NoSQL database.
NVivo - Buy NVivo now for flexible solutions to meet your specific research and data analysis needs.
Redis - Redis is an open source in-memory data structure project implementing a distributed, in-memory key-value database with optional durability.
ATLAS.ti - ATLAS.ti is a powerful workbench for the qualitative analysis of large bodies of textual, graphical, audio and video data. It offers a variety of sophisticated tools for accomplishing the tasks associated with any systematic approach to "soft" data.
ArangoDB - A distributed open-source database with a flexible data model for documents, graphs, and key-values.
QualCoder - A very complete Free and Open Source Software (FOSS) Computer-Assisted Qualitative Data Analysis Software (CAQDAS) written in Python. It works with text, images, and multimedia such as audios and videos.