Concord

A distributed, strongly-consistent embedded key-value store built in Elixir using the Raft consensus algorithm.

Concord is an embedded database for Elixir applications — think SQLite for distributed coordination. Starts with your application, no separate infrastructure needed. Strong consistency guarantees with ETS-backed read performance.

Key Features

• Strong Consistency — Raft consensus ensures all nodes agree on data
• High Performance — ETS-backed reads with microsecond-level latency
• Embedded Design — Starts with your app, no external infrastructure
• Configurable Consistency — Choose eventual, leader, or strong per operation
• TTL Support — Automatic key expiration with time-to-live
• Bulk Operations — Efficient batch processing (up to 500 items)
• Value Compression — Automatic compression for large values
• Conditional Updates — Compare-and-swap for optimistic concurrency
• Secondary Indexes — Query by indexed fields
• Backup/Restore — Compressed backups with integrity verification
• Telemetry — Built-in telemetry events for observability hooks

Installation

def deps do
  [{:concord, "~> 1.1"}]
end

Quick Start

# Store and retrieve data
Concord.put("user:1001", %{name: "Alice", role: "admin"})
{:ok, user} = Concord.get("user:1001")

# TTL (auto-expires after 1 hour)
Concord.put("session:abc", session_data, ttl: 3600)
{:ok, {data, remaining_ttl}} = Concord.get_with_ttl("session:abc")

# Bulk operations
Concord.put_many([{"k1", "v1"}, {"k2", "v2", 600}])
{:ok, results} = Concord.get_many(["k1", "k2"])

# Conditional update (compare-and-swap)
Concord.put_if("counter", 1, expected: 0)

# Read consistency levels
Concord.get("key", consistency: :eventual)  # Fast, may be stale
Concord.get("key", consistency: :leader)    # Default, balanced
Concord.get("key", consistency: :strong)    # Linearizable

Multi-Node Cluster

iex --name n1@127.0.0.1 --cookie concord -S mix  # Terminal 1
iex --name n2@127.0.0.1 --cookie concord -S mix  # Terminal 2
iex --name n3@127.0.0.1 --cookie concord -S mix  # Terminal 3

Performance

Performance varies significantly depending on hardware, cluster size, network topology, and consistency level. ETS-backed reads are inherently fast, but actual throughput and latency depend on your deployment. Run mix run benchmarks/run_benchmarks.exs on your own hardware to get representative numbers.

When to Use Concord

Use Case	Fit
Feature Flags	Excellent
Session Storage	Excellent
Distributed Locks	Excellent
Config Management	Excellent
Rate Limiting	Good
API Response Cache	Great
Primary Database	Avoid (use PostgreSQL)
Large Blob Storage	Avoid (use S3)

Comparison

Feature	Concord	etcd	Consul	ZooKeeper
Language	Elixir	Go	Go	Java
Consistency	Strong (Raft)	Strong (Raft)	Strong (Raft)	Strong (Zab)
Storage	In-memory (ETS)	Disk (WAL)	Memory + Disk	Disk
Read Latency	1-5ms	5-20ms	5-15ms	5-20ms
Embedded	Yes	No	No	No
Multi-DC	No	Yes	Yes	Yes

Documentation

• Getting Started — Installation, quick start, common use cases
• Elixir API Guide — Consistency levels, CAS, queries, compression
• Backup & Restore — Data safety and disaster recovery
• Configuration — All configuration options
• Architecture — Design blueprint

Contributing

1. Fork the repository
2. Create a feature branch
3. Add tests for new functionality
4. Ensure all tests pass (mix test)
5. Submit a pull request

License

MIT License — See LICENSE for details.

Acknowledgments

• Ra library by the RabbitMQ team
• libcluster for cluster management
• The Raft paper by Ongaro & Ousterhout