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, "~> 2.0"}]
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

Comparison

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