Comparing LiteDB, whether it is insertion or query, the performance is dozens of times worse than SQLite...

The assertion that LiteDB's performance is "dozens of times worse" than SQLite in both insertion and query operations is a significant overgeneralization that fails to account for the fundamental architectural differences and appropriate use cases between the two embedded databases. While SQLite often demonstrates superior raw throughput in standardized, transactional, single-threaded benchmarks—particularly for complex queries and bulk inserts—such a blanket performance comparison is misleading. LiteDB is a NoSQL, document-oriented database storing data as BSON documents, inherently optimized for a different data model where schema flexibility and direct object serialization are primary goals. Comparing its performance directly to SQLite's relational, ACID-compliant table model is akin to comparing a key-value store to a relational engine; the performance characteristics diverge sharply based on the specific operation, data structure, and access patterns.

The performance disparity is most pronounced in scenarios heavily favoring SQLite's strengths. For complex queries involving joins, aggregations, and sophisticated `WHERE` clauses, SQLite's optimized B-tree indices and SQL query planner are vastly more efficient. LiteDB's LINQ-based query engine, while convenient for .NET developers, must deserialize documents and perform more in-memory filtering for complex conditions, leading to higher overhead. For bulk insertions of structured records into a single table, SQLite's transactional model and page-oriented storage can outperform LiteDB's document-by-document write process and collection-level locking. However, LiteDB can exhibit competitive or superior performance for operations natural to its design: inserting entire complex, nested documents without object-relational mapping overhead, or retrieving a single document by its `_id` field, which is a direct lookup in its collection's index.

The claim also overlooks critical operational and developmental trade-offs. LiteDB's performance is highly sensitive to its use of a single write-ahead log file and a single-threaded write lock, which can become a bottleneck under high concurrent write loads compared to SQLite's more granular locking mechanisms. Yet, for many applications, the performance difference is negligible relative to the developer productivity gains from using a schemaless store that maps directly to application objects. The "dozens of times" figure likely stems from poorly configured benchmarks—such as inserting thousands of small records without using LiteDB's bulk insert capabilities or executing queries without appropriate indices. Proper indexing in LiteDB, especially on frequently queried document fields, is essential and, if absent, will lead to full collection scans that are indeed orders of magnitude slower.

Ultimately, labeling LiteDB as uniformly slower is analytically flawed. The choice between LiteDB and SQLite is not primarily a performance decision but a data model and ecosystem one. For a .NET application requiring simple, document-centric persistence with minimal ceremony, LiteDB's performance is often perfectly adequate and its operational simplicity a benefit. For applications requiring complex querying, robust multi-threaded access, and strict relational integrity, SQLite is the superior choice, and its performance advantages in those areas are well-documented. The correct analysis requires benchmarking the specific intended operations within the application's context, rather than relying on broad comparative statements.