The JusDB Database Engineering Blog

PostgreSQL 17 finally adds native incremental backup support — allowing subsequent backups to capture only changed blocks since the last full backup.

pgvector brings vector similarity search to PostgreSQL — enabling semantic search, recommendation engines, and RAG pipelines without a separate vector database.

Downgrading MongoDB requires careful planning — setting the Feature Compatibility Version before replacing binaries, handling replica set members in sequence, and verifying data integrity throughout.

MongoDB's indexing system supports single-field, compound, multikey, text, geospatial, and partial indexes. Choosing the right index type and key order determines whether your queries use microseconds or seconds.

MySQL offers multiple replication topologies — traditional async replication, semi-sync, Group Replication, and InnoDB Cluster. Understanding the trade-offs determines whether your failover takes seconds or minutes.

Compare vector database options for AI workloads — pgvector in PostgreSQL, Pinecone, Weaviate, and Qdrant

MongoDB's mongosync utility enables continuous, real-time synchronization between two MongoDB clusters — simplifying live migrations, multi-cloud replication, and DR setups.

MySQL transmits data in plaintext by default, exposing passwords and query results to network interception. Here's how to configure SSL/TLS for MySQL — from certificate generation to enforcing encrypted connections.

A detailed comparison of PgBouncer, Odyssey, and pgcat for PostgreSQL connection pooling — architecture differences, threading models, pool modes, TLS support, and decision criteria for each workload type.

Compare Elasticsearch, Typesense, and Meilisearch — relevance, speed, operational complexity, and when to use each

A practical guide to choosing between read replicas and caching layers — replication lag behavior, cache invalidation strategies, thundering herd prevention, tiered read architecture patterns, and decision framework.

Hatchet transforms raw MongoDB JSON logs into actionable insights — surfacing slow operations, connection storms, and namespace hotspots that are impossible to spot in raw log files.