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Based on our record, BoltDB should be more popular than Google Cloud Bigtable. It has been mentiond 13 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.
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
Cloud Bigtable: Petabyte-scale, low-latency, non-relational 🔗Link 🔗Link. - Source: dev.to / over 1 year ago
> 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 / over 1 year ago
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
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
This crate started out as just a way for me to learn how boltdb works, while learning Rust at the same time. But somehow people started finding and using it and seem to like the simple API, so I figured I might as well share it in case someone else finds it useful too. If you want to know more about my motivations and the history of this crate, you can read the release notes on version 0.8.0! Source: about 1 year ago
Some example of embeddable database could be genji, badger and boltdb. Source: over 1 year ago
Designing Data Intensive applications- specifically chapter 3 and 4 which deal with strategies and algorithms for storing and encoding data to be stored on disk and their pros and cons. Once you read that, I'll suggest reading the source of a simple embedded key-value database, I wouldn't bother with RDBMs as they are complex beasts and contain way more than you need. BoltDB is a good project to read the source of... - Source: Hacker News / over 1 year ago
Bolt db and Bolt db's author post to go with it. Source: over 1 year ago
The litestream project was created by https://github.com/benbjohnson who wrote https://github.com/boltdb/bolt (a key value store) which has been instrumental (from my point of view) in the Go community as one of the first choices for an embedded database as it had the idea of transactions and views. It was used by https://github.com/blevesearch/bleve, https://github.com/etcd-io/etcd, and number of other projects. - Source: Hacker News / about 2 years ago
Amazon DynamoDB - Amazon DynamoDB is a fully managed NoSQL database service offered by Amazon.
Redis - Redis is an open source in-memory data structure project implementing a distributed, in-memory key-value database with optional durability.
MongoDB - MongoDB (from "humongous") is a scalable, high-performance NoSQL database.
Aerospike - Aerospike is a high-performing NoSQL database supporting high transaction volumes with low latency.
ArangoDB - A distributed open-source database with a flexible data model for documents, graphs, and key-values.
Amazon Aurora - MySQL and PostgreSQL-compatible relational database built for the cloud. Performance and availability of commercial-grade databases at 1/10th the cost.