Google Cloud Spanner VS Apache Thrift

Multiregion is possible in Google Cloud using Cloud Spanner, which allows you to replicate the database not only in multiple zones but also in multiple regions as defined in the instance configuration. The replicas allow you to read data with low latency from multiple locations that are close to or within the region in the configuration. - Source: dev.to / 10 months ago

Basically everything I touch is in-house, but a majority of it is available publicly. For instance: https://cloud.google.com/spanner/. Source: over 1 year ago

An application that needs to handle a lot of data can use a distributed database like Cloud Spanner. Unlimited scale and you don't have to split your database into multiple tables. Source: over 1 year ago

Look at the architecture and performance of Google's Cloud Spanner, a CP system with 99.999% availability... https://cloud.google.com/spanner. Source: over 1 year ago

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

While gRPC and Apache Thrift have served the microservice architecture well, CloudWeGo's advanced features and performance metrics set it apart as a promising open source solution for the future. - Source: dev.to / 3 months ago

Services in general communicate via Thrift (and in some cases HTTP). Source: about 1 year ago

Protocol Buffers is the most popular one, but there are many others such as Apache Thrift and my own Typical. Source: about 1 year ago

RPC is not strictly OO, but you can think of RPC calls like method calls. In general it will reflect your interface design and doesn't have to be top-down, although a good project usually will look that way. A good contrast to REST where you use POST/PUT/GET/DELETE pattern on resources where as a procedure call could be a lot more flexible and potentially lighter weight. Think of it like defining methods in code... Source: over 1 year ago

The information can be stored in a database or as files, serialized in a standard format and with a schema agreed with your Data Engineering team. Depending on your information and requirements, it can be as simple as CSV, XML or JSON, or Big Data formats such as Parquet, Avro, ORC, Arrow, or message serialization formats like Protocol Buffers, FlatBuffers, MessagePack, Thrift, or Cap'n Proto. - Source: dev.to / over 1 year ago