I did a talk about establishing criteria for differences between distributed SQL and NoSQL databases. https://www.youtube.com/watch?v=nJvnq8ZD_7Q https://www.y

I did a talk about establishing criteria for differences between distributed SQL and NoSQL databases. https://www.youtube.com/watch?v=nJvnq8ZD_7Q https://www.youtube.com/watch?v=nJvnq8ZD_7Q There are a couple of different dimensions to consider. I didn't focus on this in the talk but firstly you should consider these elements... • Speed (latency & throughputs) • Scale (gigabytes? terabytes? petabytes? exabytes?) • Workload types (OLAP, OLTP, HTAP, data warehouses/lakes/lakehouses) • Consistency Models ("ACID vs. BASE", eventual vs. strong, etc.) • Data Model - RDBMS, NoSQL (Key-Value, Wide Column, Document, Graph, Column Store, etc.) • Query Language (SQL, streaming SQL [Flink], CQL [Cassandra, ScyllaDB, DataStax, CosmosDB, Keyspaces, Yugabyte, etc.], Gremlin/Tinkerpop [JanusGraph, DSE Graph, OrientDB, etc.], and so on. What I did focus on was more the "distributed system" attributes... • Clustering & distribution (local clustering, cross-clustering, multidatacenter clustering) • Node roles, high availability & failover strategies (primary/replica, peer-to-peer leaderless/active-active, load balancing) • Data replication/sharding strategies (replication factors, consistency levels, manual vs. auto-sharing, topology awareness [rack and datacenter awareness]) I only focused on a handful. There are literally hundreds of databases tracked on DB-engines: https://db-engines.com/en/ranking https://db-engines.com/en/ranking [Disclosure, I work for ScyllaDB]