Trending Databases repositories

The full ecosystem in one list: SQL engines, NoSQL stores, vector databases for AI search, time-series engines, columnar / analytical databases, and the embedded engines (SQLite, DuckDB) bridging in-process queries with distributed systems. The leaderboard mixes them because adoption mixes them — a Postgres + pgvector stack competes with a dedicated vector engine for the same use case, and the score lets both rank fairly. The community keeps consolidating around Postgres + extensions as the default for most workloads, with the long tail of specialised engines (vector, time-series, graph) earning slots by being meaningfully better at one thing. The AI-tooling wave drove heavy investment into vector engines and embedded databases — they rank alongside the historical SQL incumbents because that's where the live momentum is. Reading the list, the most useful filter is workload shape: transactional, analytical, vector-heavy, time-series-heavy, or general-purpose.