Currently MySQL and PostgreSQL databases are fully supported. MongoDB supports inserts and deletes, however, updates return a copy of the operation (for example, a $rename operation will return a $set for the new field and an $unset for the old field) instead of the object as it exists in the database. Redis support is on the way. Lapidus can currently be used as a daemon or Node.js module. Support for piping line-delimited JSON to other processes is a high priority.

You'll need PostgreSQL 9.4 or higher with logical replication configured and the decoding_json plugin installed and loaded. Forks of PostgreSQL should be compatible provided they ship with pg_recvlogical.

To install the decoding_json logical decoding plugin on Ubuntu:

# Ubuntu / Debian
git clone https://github.com/leptonix/decoding-json.git
cd decoding-json
sudo apt-get install postgresql-server-dev-9.5
make
sudo cp decoding_json.so /usr/lib/postgresql/9.5/lib/

To enable logical decoding and the decoding_json plugin add the following lines to your postgresql.conf:

wal_level = logical
max_wal_senders = 10
max_replication_slots = 10
shared_preload_libraries = 'decoding_json'

Create a user with replication privileges and add them to your pg_hba.conf file.

Afterwards, restart PostgreSQL and verify that it starts correctly:

service postgresql restart
service postgresql status

WARNING: PostgreSQL will hold onto the WAL logs until all logical replication slots have consumed their data. This means that if you try out Lapidus and fail to delete your slot that you'll likely run out of disk space on your system.

For information on managing replication slots: consult the documentation.

You'll need MySQL 5.1.15 or higher with binary logging configured. Forks of MySQL should be compatible but have not been tested.

Add the following lines to your my.cnf:

server-id        = 1
log_bin          = /var/log/mysql/mysql-bin.log
max_binlog_size  = 100M  # WARNING: make sure to set this to a sane value or you may fill your disk
expire_logs_days = 10    # Optional
binlog_format    = row

Create a user with replication permissions:

GRANT REPLICATION SLAVE, REPLICATION CLIENT, SELECT ON *.* TO 'lapidus'@'localhost' IDENTIFIED BY 'secure-password';

Restart MySQL and verify that it starts correctly:

service mysql restart
service mysql status

We test against MongoDB 3.x, however, older versions should work. You'll need to setup MongoDB as a replica set. If you're not truly using replication during development you will need to connect and run:

// DO NOT DO THIS IN PRODUCTION
rs.initiate()
db.getMongo().setSlaveOk();

For more information on setting up replication in MongoDB check out the docs.

Lapidus will search for lapidus.json in the current working directory. You can specify a different configuration by passing it to the constructor or using the -c flag on the terminal. For a list of command line options run lapidus --help.

Here is a sample configuration file that will connect to two PostgreSQL backends, two MySQL backends, one MongoDB backend and publish all events to NATS using the NATS plugin:

{
  "backends": [
    {
      "type": "mysql",
      "hostname": "127.0.0.1",
      "username": "jacob",
      "database": "jacob",
      "password": "2PQM9aiKMJX5chv76gYdFJNi",
      "serverId": 1
    },

    {
      "type": "mysql",
      "hostname": "127.0.0.1",
      "username": "sawyer",
      "database": "sawyer",
      "password": "2PQM9aiKMJX5chv76gYdFJNi",
      "serverId": 2
    },

    {
      "type": "postgresql",
      "host": "127.0.0.1",
      "user": "lapidus",
      "database": "lapidus",
      "password": "2PQM9aiKMJX5chv76gYdFJNi",
      "slot": "lapidus_slot"
    },

    {
      "type": "postgresql",
      "host": "127.0.0.1",
      "user": "hurley",
      "database": "hurley",
      "password": "2PQM9aiKMJX5chv76gYdFJNi",
      "slot": "hurley_slot"
    },
    
    {
      "type": "mongo",
      "hostname": "127.0.0.1",
      "username": "lapidus",
      "database": "lapidus",
      "password": "2PQM9aiKMJX5chv76gYdFJNi",
      "replicaSet": "rs0"
    }
  ],
  "plugins": {
    "nats": {
      "server": "nats://localhost:4222"
    }
  }
}

Lapidus ships with a lightweight NATS plugin. NATS is an open-source, high-performance, lightweight cloud native messaging system.

###Configuration

Publish to NATS for all backends (one connection per backend):

{
  "backends": [...]
  ],
  "plugins": {
    "nats": {
      "server": "nats://localhost:4222"
    }
  }
}

Publish to NATS for a specific backend:

{
  "backends": [
    {
      "type": "postgresql",
      "host": "the.hatch",
      "user": "desmond",
      "database": "darma",
      "password": "notpennysboat123",
      "slot": "walts_raft",
      
      "plugins": {
        "nats": {
          "server": "nats://localhost:4222"
        }
      }
    }
  ]
}

Insert, Update and Delete events will be published using the subject schema.table.pk. Here are examples events:

Insert:

// TODO: sample insert

Update:

// TODO: sample update

Delete:

// TODO: sample delete

• At this time, transactions and other event types are not published to NATS.
• Each worker uses its own connection to NATS using non-blocking event emitters; out of order delivery is likely.
• NATS does not guarantee in order delivery so a blocking variant is not likely (it's 10-20 LoC if you're interested).

Lapidus is currently under heavy development. It is deployed with 1250 simultaneous users on very modest hardware using the MySQL and PostgreSQL backends and NATS plugin. Typical latency between MySQL -> Lapidus -> NATS is 1ms - 3ms. Please share your results. Benchmark and load testing scripts will be made available.

CPU usage is light, as a rule of thumb, measure your peak MySQL CPU usage (after enabling binary logging) and multiply that by 0.075. That's how much CPU Lapidus is likely to use at peak.

Generally speaking, each worker requires 10-15 MB of ram.

Your peak memory usage is dictated by V8's garbage collection. When running the TPC-C benchmark against the MySQL worker using 8 cores memory sat around 70MB and peaked at 120MB before garbage collection knocked it back down to 70MB.

I tested for memory leaks by running 5 million transactions using the TPC-C benchmark and things look pretty solid, if you notice any issues please report them.

Lapidus is MIT licensed. The artwork in the header is Copyright Matt Greenholt.

Matt Greenholt has kindly allowed the use of his artwork. Check out his blog and flickr.