A distributed SQLite replicator.


What is it useful for right now?

If you are using SQLite as ephemeral storage, or a scenario where eventual consistency is fine for you. Marmot can give you a solid replication between your nodes as Marmot builds on top of fault-tolerant consensus protocol (Multi-Group Raft), thus allowing robust recovery and replication. This means if you are running a medium traffic website based on SQLite you should be easily able to handle load without any problems. Read heavy workloads won’t be bottle-neck at all.



go build -o build/marmot ./marmot.go

Make sure you have 2 SQLite DBs with exact same schemas (ideally empty):

build/marmot -bootstrap [email protected]:8162 -bind -bind-pane localhost:6001 -node-id 1 -replicate table1,table2 -db-path /tmp/cache-1.db
build/marmot -bootstrap [email protected]:8161 -bind -bind-pane localhost:6002 -node-id 2 -replicate table1,table2 -db-path /tmp/cache-2.db


Marmot is picks simplicity, and lesser knobs to configure by choice. Here are command line options you can use to configure marmot:

  • cleanup – Just cleanup and exit marmot. Useful for scenarios where you are performing a cleanup of hooks and change logs. (default: false)
  • db-path – Path to DB from which given tables will be replicated. These tables can be specified in replicate option. (default: /tmp/marmot.db)
  • replicate – A comma seperated list of tables to replicate with no spaces in between (e.g. news,history) (default: [empty])
  • node-id – An ID number (positive integer) to represent an ID for this node, this is required to be a unique number per node, and used for consensus protocol. (default)
  • bind – A host:port combination of listen for other nodes on (default:
  • raft-path – Path of directory to save consensus related logs, states, and snapshots (default: /tmp/raft)
  • shards – Number of shards over which the tables will be replicated on, marmot uses shards to distribute the ownership of replication. Which allows you to distribute load over multiple nodes rather than single master. By default, there are 16 shards which means you should be easily able to have upto 16 master nodes. Beyond that you should this flag to have a bigger cluster. Higher shards also mean more disk space, and memory usage per node. Ideally these shards should be elastic (to be implemented).
  • bootstrap – A comma seperated list of initial bootstrap nodes <node_id>@<ip>:<port> (e.g. [email protected]:8162,[email protected]:8163 will specify 2 bootstrap nodes for cluster).
  • bind-pane – A host:port combination for control panel address (default: localhost:6010). All the endpoints are basic auth protected which should be set via AUTH_KEY env variable (e.g. AUTH_KEY='Basic ...'). This address should not be a public accessible, and should be only used for cluster management. This in future will serve as full control panel hosting and cluster management API.
  • verbose – Specify if system should dump debug logs on console as well. Only use this for debugging.

How does it work?

Marmot works by using a pretty basic trick so that each process that’s access database can capture changes, and then Marmot can publish them to rest of the nodes. This is how it works internally:

  • Each table gets a __marmot__<table_name>_change_log that will record a every change via triggers to change log.
  • Each table gets insert, update, delete triggers in that kicks in AFTER the changes have been committed to the table. These triggers record OLD or NEW values into the table.

When you are running Marmot process, it’s watching for changes on DB file and WAL file. Everytime there is a change Marmot scans these tables to publish them to other nodes in cluster by:

  • Gather all change records, and for each record calculate a consistent hash based on table name and primary keys.
  • Using the hash decide the primary shard the change belongs to.
  • Propose the change to the cluster.
  • As soon as quorum of nodes apply the change to local tables change is considered committed, and remove from change log table. These changes are applied in an upsert manner, meaning each tuple due to consensus will have one deterministic order of changes getting applied in case or race-condition. So it’s quite possible that a change committed locally is overwritten because it was not the last one in.


Right now there are a few limitations on current solution:

  • Only incremental, change stream i.e. tables should exist with matching schema, and existing rows won’t be copied over. SQLite tools are enough for that.
  • Only WAL mode supported.
  • Won’t create DB file if it doesn’t exist.
  • Right now no support for copying previous data of table into existing table, or copy schema. Would be introduced in future though.

Production status

Being used for ephemeral cache storage in production services, on a very read heavy site. You can view my personal status board here. Here is an image from a production server running Marmot:



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