Google Cloud Storage
Minio
Amazon S3
Azure Blob Storage
DigitalOcean Spaces
IBM Cloud Object Storage
Zadara Storage
Amazon Simple Storage Service (S3)
Apache Cassandra
MongoDB
Redis
ArangoDB
PostgreSQL
neo4j
OrientDB
Azure Cosmos DB
Google Cloud StorageNo Google Cloud Storage videos yet. You could help us improve this page by suggesting one.
Apache Cassandra might be a bit more popular than Google Cloud Storage. We know about 40 links to it since March 2021 and only 36 links to Google Cloud Storage. 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.
Cloud Storage: blog storage for static assets and media files. - Source: dev.to / 4 months ago
Preevy includes built-in support for saving profiles on AWS S3 and Google Cloud Storage. You can also store the profile on the local filesystem and copy it manually before running Preevy - we won't show this method here. - Source: dev.to / 5 months ago
Google Cloud Storage{:target="_blank"} is a globally distributed object storage service offered by Google Cloud Platform. They provide trustworthy and scalable databases for storing large amounts of blob data. They also provide a way to optimize cost and performance with different storage classes and pricing options. - Source: dev.to / 10 months ago
Google Cloud Storage - https://cloud.google.com/storage/. - Source: dev.to / 10 months ago
Also, in terms of packing a pre-trained model you will probably want to puts weights, biases etc into S3 or similar object storage (https://cloud.google.com/storage etc) and load it on application start. Source: 11 months 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 / 24 days 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 / 2 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 / 8 months ago
To use NoSQL databases with code, you first need to choose a NoSQL database that suits your requirements. Some popular examples of NoSQL databases are MongoDB, Cassandra, Redis, and DynamoDB. Each of these databases has its own set of APIs and drivers that can be used to interact with them. Here, I'll use MongoDB as an example and explain how to perform CRUD operations using Python and its PyMongo package. - Source: dev.to / about 1 year ago
Minio - Minio is an open-source minimal cloud storage server.
MongoDB - MongoDB (from "humongous") is a scalable, high-performance NoSQL database.
Amazon S3 - Amazon S3 is an object storage where users can store data from their business on a safe, cloud-based platform. Amazon S3 operates in 54 availability zones within 18 graphic regions and 1 local region.
Redis - Redis is an open source in-memory data structure project implementing a distributed, in-memory key-value database with optional durability.
Azure Blob Storage - Use Azure Blob Storage to store all kinds of files. Azure hot, cool, and archive storage is reliable cloud object storage for unstructured data
ArangoDB - A distributed open-source database with a flexible data model for documents, graphs, and key-values.
