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CyborgDB transforms traditional databases into Confidential Vector Databases by leveraging their storage capabilities while adding encrypted vector search functionality. Choose the backing store that best fits your existing infrastructure and operational requirements. CyborgDB RAG Overview
v0.17 storage surface. CyborgDB now supports memory, disk (RocksDB), and s3 (AWS S3 or any S3-compatible store) across both deployment models. The previous PostgreSQL and Redis backends have been removed.

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Amazon S3

Available in: Service · Embedded Scalable cloud object storage for distributed deployments CyborgDB supports Amazon S3 (and S3-compatible stores such as MinIO) as a backing store, enabling fully cloud-native deployments without managing a traditional database server.

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Key Benefits

Infinite Scalability
Object storage scales seamlessly with your data — no capacity planning or provisioning required. Managed Infrastructure
No database servers to patch, tune, or back up. AWS handles availability and durability. S3-Compatible
Works with AWS S3, MinIO, Cloudflare R2, and any other S3-compatible object store. Best For: Cloud-native deployments, multi-region architectures, and workloads that already rely on object storage infrastructure.

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Disk (RocksDB)

Available in: Service · Embedded
The embedded libraries refer to this backend as “RocksDB”. CyborgDB Service v0.17 selects it via CYBORGDB_DB_TYPE=disk (and it is the default).
Persistent local storage for single-node deployments The disk backend provides persistent key-value storage directly on local disk via embedded RocksDB, with no network dependency. This makes it the recommended backing store for single-node CyborgDB deployments where simplicity and reliability are priorities.

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Key Benefits

No Network Dependency All data is stored locally on disk — no external database servers to configure or manage. Persistent Storage Data survives process restarts with automatic durability via write-ahead logging. Optimized for Embedded Use Low memory footprint with filesystem support. Best For: Embedded/local deployments, single-machine applications, edge devices, and scenarios where you want persistent storage without external infrastructure.

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Memory

Available in: Service · Embedded
The embedded libraries refer to this backend as “ThreadSafeMemory”. CyborgDB Service v0.17 selects it via CYBORGDB_DB_TYPE=memory.
Local in-process storage for development and testing Memory-based storage keeps all data in local process memory, providing the fastest possible access with zero network overhead. Perfect for development, testing, and single-process applications.

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Key Benefits

Zero Network Latency
Direct memory access without serialization overhead for maximum performance. Development Simplicity
No external dependencies or configuration required — instant setup for prototyping. Deterministic Performance
Predictable access patterns with complete control over memory usage. Best For: Development and testing environments, single-process applications, proof-of-concept scenarios, and ephemeral data requirements.

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Managed Services Support

CyborgDB works seamlessly with managed object storage services, reducing operational overhead while maintaining security and performance.

AWS

Amazon S3
Scalable object storage with 11 nines of durability

Cloudflare

Cloudflare R2
S3-compatible object storage with zero egress fees

Self-hosted

MinIO
S3-compatible object storage you control end-to-end

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Choosing the Right Backing Store

  • Single-node deployment — You want persistent local storage with no external dependencies
  • Edge devices — Running on hardware without network access to databases
  • Simplicity — You want a single-binary deployment with built-in storage
  • Local development — Persistent storage that survives restarts without infrastructure
  • Default choice — It’s the v0.17 service default and works out of the box

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Configuration Examples

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Embedded library

RocksDB
from cyborgdb_core import DBConfig

# Local RocksDB (default path: ~/.cyborgdb/data)
db_config = DBConfig("rocksdb")
S3
from cyborgdb_core import DBConfig

# AWS S3
db_config = DBConfig("s3://my-bucket?region=us-east-1")

# AWS S3 with explicit credentials
db_config = DBConfig("s3://my-bucket?region=us-east-1&access_key=AKID...&secret_key=...")

# MinIO (S3-compatible)
db_config = DBConfig("s3://my-bucket?region=us-east-1&endpoint=http://localhost:9000&access_key=minioadmin&secret_key=minioadmin")
ThreadSafeMemory
from cyborgdb_core import DBConfig

# Thread-safe in-memory storage
db_config = DBConfig("threadsafememory")

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Service

Select via the CYBORGDB_DB_TYPE environment variable (or the equivalent YAML key). See Environment Variables for the full list. 
# disk (default)
export CYBORGDB_DB_TYPE=disk
export CYBORGDB_DISK_PATH=/var/lib/cyborgdb   # optional

# s3
export CYBORGDB_DB_TYPE=s3
export CYBORGDB_S3_BUCKET=my-bucket
export CYBORGDB_S3_REGION=us-east-1

# memory
export CYBORGDB_DB_TYPE=memory

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Performance Characteristics

Backing StoreLatencyThroughputDurabilityConsistency
Memory / ThreadSafeMemory~1µsVery HighNoneSingle Process / Thread-Safe
RocksDB (disk)~10µsHighLocal DiskSingle Process
S3~10msMediumFull (11 nines)Eventual
Choose based on your application’s specific requirements for speed, durability, and consistency.