NeorunBase Key Features
A PostgreSQL-compatible multi-modal Lakebase that handles relational, JSONB, vector database, full-text search, graph database, and spatial data in a single distributed ACID engine. No separate Pinecone, Elasticsearch, or Neo4j — all signals combine in one SQL statement, with multi-site DR, silent-fail safety, and topology-aware placement built in for enterprise operations.
PostgreSQL-Compatible Distributed SQL
A distributed SQL engine that speaks the PostgreSQL wire protocol, so psql, JDBC and BI tools connect unchanged. Relational and JSONB data scale out with hash sharding.
Distributed Transactions and HA
2PC distributed ACID transactions on RocksDB, online resharding, leader election and replica read failover keep the service up through failures.
Vector Search
pgvector-compatible VECTOR type and distance operators with distributed HNSW indexes. Embeddings and business data live in the same transaction.
Full-Text Search
Lucene BM25 indexes with PostgreSQL-compatible @@ and ts_rank, a Korean Nori analyzer, and hybrid search that combines keywords with vectors.
Graph Traversal and Analytics
BFS neighbor traversal, path-existence checks and PageRank as SQL functions, ideal for Graph RAG that reranks search results by graph proximity.
Geospatial
PostGIS-compatible spatial functions such as ST_Distance and ST_Contains with a spatial index, for location-aware services in the same engine.
Iceberg CDC and Lakehouse Serving
Syncs OLTP changes to Iceberg automatically and ingests from Kafka. Serves Iceberg tables in place with low-latency primary-key lookups and runs DML on them.
Multiple Catalogs
Register the built-in catalog and several Iceberg catalogs with CREATE CATALOG and query them together in one SQL statement.
Enterprise Security
AES-256-GCM envelope encryption with a built-in KMS, TLS, IAM policies with column masking and row filters, SSO (OIDC, SAML, LDAP) and Ontul IAM federation.
Disaster Recovery and Operations
Multi-site async replication, S3 backup and restore, zone- and rack-aware replica placement with automatic repair, Prometheus metrics and a web console.
Use Cases
Graph RAG & Agent Retrieval
Hard Filter (SQL WHERE) + semantic/keyword hybrid retrieval + graph-based re-ranking (structural — by graph proximity) + fact-check, all in a single SELECT. Skip the four-system stack (Postgres + Pinecone + Elasticsearch + Neo4j) and run RAG / agent retrieval from one database.
Knowledge Graph & Ontology Store
Model entities and relationships as ordinary tables; traverse with BFS, score with PageRank / Personalized PageRank. RBAC, transactions, and backup come for free — no separate graph DB to operate.
Unified OLTP & Analytics
OLTP transactions auto-sync to Iceberg via CDC, and Ontul / Trino / Spark analyse the same data. No bespoke ETL or CDC pipeline to maintain.
Large-Scale Distributed DB & Real-Time Ingest
Horizontal sharding with automatic rebalancing plus direct Kafka ingestion handles petabyte-scale transactional workloads.
Location-Aware & Geo RAG
Combine PostGIS-compatible spatial functions with vector embeddings for location-based recommendation, GIS, and geo-aware retrieval — all in one engine.
Considering NeorunBase for your data platform?
OLTP · Vector DB · FTS · Graph DB · Spatial · DR — One ACID SQL Engine.
Multi-modal data — vector DB, graph DB, and multi-site DR — in one PostgreSQL-compatible engine.