Google Cloud Bigtable Reviews

Minio Reviews

Google Cloud Bigtable mentions (6)

• Vaultree and AlloyDB: the world's first Fully Homomorphic and Searchable Cloud Encryption Solution

  In my opinion, Google has built some fantastic database services like Bigtable and Spanner, which literally changed the industry for good, and I am eager to see how they will build upon this new service. With AlloyDB's disaggregated architecture, the dystopian world where I only pay for SQL databases per query and the stored data on GCP seems closer than ever. - Source: dev.to / over 1 year ago

• Google Cloud Reference

  Cloud Bigtable: Petabyte-scale, low-latency, non-relational 🔗Link 🔗Link. - Source: dev.to / almost 2 years ago

• A Graph-Based Firebase

  > These triples say that the Layer with id 1 has a fontSize 20 and backgroundColor blue. Since they are different rows, there’s no conflict. This sounds a lot like Bigtable (https://cloud.google.com/bigtable), which also does last-write-wins conflict resolution layer. So this is adding a GraphQL + frontend layer to it? - Source: Hacker News / almost 2 years ago

• The 4 Types of NoSQL Databases You Need to Know

  Google's BigTable paper inspired this database design, and it is capable of handling large data loads on distributed machines. In addition, column-oriented databases provide efficient compression and high performance with aggregated queries such as sum, average, and minimum. - Source: dev.to / almost 2 years ago

• Can someone help me understand why data batch processing and data streaming processing pose such different challenges in data management?

  Because of these and other differences, the tools used are also different. With batch processing, data might be read from large files, processed, and stored in an OLTP (Online Transaction Processing) database (like MySQL) or OLAP (Online Analytical Processing) system (like Google BigQuery). But these would not be good solutions for streaming applications, because they are not optimized for high throughput on a lot... Source: over 2 years ago

Minio mentions (156)

• A step-by-step guide to building an MLOps pipeline

  The meta-data and model artifacts from experiment tracking can contain large amounts of data, such as the training model files, data files, metrics and logs, visualizations, configuration files, checkpoints, etc. In cases where the experiment tool doesn't support data storage, an alternative option is to track the training and validation data versions per experiment. They use remote data storage systems such as S3... - Source: dev.to / 18 days ago

• S3 Is Showing Its Age

  > When it gets too out of hand, people will paper it over with a new, simpler abstraction layer, and the process starts again, only with a layer of garbage spaghetti underneath. I'm pretty happy that there are S3 compatible stores that you can host yourself, that aren't insanely complex. MinIO: https://min.io/ SeaweedFS: https://github.com/seaweedfs/seaweedfs Of course, many will prefer hosted/managed solutions... - Source: Hacker News / about 1 month ago

• deploying a minio service to kubernetes

  Here are the basic steps to getting a minio tenant deployed inot kubernetes. There are some pre-requisites tasks to be deployed (and will not be covered in this article) including. - Source: dev.to / 2 months ago

• Ceph: A Journey to 1 TiB/s

  I'd throw minio [1] in the list there as well for homelab k8s object storage. [1] https://min.io/. - Source: Hacker News / 5 months ago

• Opinions sought: unknown data transfer

  Can you just append the data to a blob using something like the s3 blob api? AWS, Azure and Minio https://min.io/ all support it. That way you don't have to reinvent the wheel. Source: 10 months ago