Rethinking Database Architecture
entropyDB is built to solve the fundamental problem of modern data infrastructure: why should developers juggle multiple databases when one unified platform can do it all?
Our Mission
Provide a single database platform that supports relational, document, key–value, time-series, graph and vector data models with strong, configurable guarantees and integrated AI/ML features.
We're reducing operational overhead and enabling rapid AI-driven product development by eliminating the complexity of polyglot persistence.
Why We Built entropyDB
Modern applications need multiple data models, but managing separate databases creates operational nightmares and integration challenges.
The Problem
Developers use 5-10 different databases: Postgres for transactions, Elasticsearch for search, Redis for caching, Pinecone for vectors, Neo4j for graphs. Each adds latency, cost, and operational burden.
The Gap
No mainstream database offers first-class support for all data models with AI-native features, deterministic transactions, and transparent storage tiering in a single engine.
Our Solution
entropyDB unifies six data models with built-in vector search, ML feature store, and operational automation. One platform, one query language, one team to manage.
Core Principles
Correctness First
Strong ACID guarantees by default. Serializability without compromise. Deterministic execution for reproducible results.
Performance Matters
Sub-millisecond P99 latency. Millions of vector operations per second. Intelligent query optimization across models.
Operations Automation
Self-healing clusters. Auto-sharding and rebalancing. Zero-downtime upgrades. You focus on apps, we handle infrastructure.
Developer Experience
Postgres compatibility. Unified query language. Rich client libraries. Comprehensive documentation. Quick time to production.
Cost Efficiency
Transparent tiered storage. Reduce TCO by 70% vs. polyglot stacks. Pay for what you use, no hidden fees.
Enterprise Ready
SOC2, HIPAA, GDPR compliance. Field-level encryption. RBAC and audit trails. Data lineage and governance.
Built on Cutting-Edge Research
entropyDB combines the best ideas from distributed systems research and production systems
Calvin-Inspired Transactions
Deterministic global ordering eliminates expensive distributed locks and 2PC in most cases. Inspired by Yale's Calvin protocol.
Hybrid Storage Engine
LSM for writes, B-tree for reads, columnar for analytics. Like RocksDB meets Postgres meets Parquet.
Sharded Vector Indexing
HNSW + IVF hybrid with distributed reranking. Scale to billions of vectors with consistent low latency.
Raft Consensus
Per-shard Raft groups for replication. Small metadata quorum for coordination. Proven reliability.
Join Our Mission
We're building the future of data infrastructure. Help us make it happen.