Introduction - OpenData<br>Skip to main content<br>OpenData home page
Search...
⌘K
Concepts
Introduction
Architecture
Writing Data
Reading Data
Storage
Deployment
Timeseries
Timeseries
Quickstart
Storage design
Configuration
Stateless Ingest
Getting to Production
API reference
Log
Log
Quickstart
Storage design
Getting to Production
API reference
Vector
Vector
Quickstart
Data Model
Storage Design
Getting to Production
API reference
Key-Value
Key-Value
Buffer
Buffer
Architecture
Configuration
Discord
opendata-oss/opendata
OpenData home page
Search...
⌘K
Search...
Navigation<br>Concepts<br>Introduction
Documentation Index<br>Fetch the complete documentation index at: https://opendata.dev/docs/llms.txt<br>Use this file to discover all available pages before exploring further.
OpenData is a collection of operationaly simple, open source databases that<br>share a unified storage foundation on object storage.<br>Database software is often available for free as open source, but the real cost<br>comes from the operational expertise required to keep them running. Operators<br>must understand and configure behavior for replication, failover, backup,<br>capacity planning, and disaster recovery. These concerns multiply with every<br>additional database system since each ship with their own implementations.<br>Is there a better way? We believe that the general avaialbility of Object<br>Storage is the escape hatch. Services like S3 provide durability, replication,<br>and availability at commodity prices with no operational overhead. When you<br>push replication and durability down to the storage layer, the database itself<br>becomes dramatically simpler. Entire categories of complexity disappear:
Durability & Availability : opendata systems can be deployed in production with a<br>single replica and still maintain durability and high write availability.
Failover & Scaling : worker nodes are stateless and only use local<br>disks for caching, making failovers and horizontal scaling trivial.
Backups & Branches : all data is stored immutably, so backups and branches<br>are as easy as marking data immune to garbage collection.
Cost to Serve : object storage is not only less expensive than replicated disks,<br>it also provides free cross-zone data transfer for ingestion and replication.
By implementing these patterns once in SlateDB, we can<br>share them across all databases in the OpenData family and provide a unified<br>operational experience.
Databases
svg]:size-6" data-component-part="card-icon"><br>Timeseries<br>Prometheus-compatible metrics database
svg]:size-6" data-component-part="card-icon"><br>Log<br>Key-oriented event streaming
svg]:size-6" data-component-part="card-icon"><br>Vector<br>SPANN-style approximate nearest neighbor search
svg]:size-6" data-component-part="card-icon"><br>Key-Value<br>Simple, low-latency key-value storage
svg]:size-6" data-component-part="card-icon"><br>Buffer<br>Highly-available ingestion buffer
Architecture
Next
⌘I