This guides provides a step-by-step procedure through your very first ToroDB Stampede sandbox installation. It also covers installation and dummy configuration of MongoDB and PostgreSQL. The sole purpose of this guide is to give ToroDB Stampede a quick try. For other purposes, read the installation and configuration chapters.

In case of any problems, consult the Trouble Shooting Guide


ToroDB Stampede requires a Java 8 runtime environment.


The following is a short step-by-step guide to install MongoDB with a single-node replica set. In case of doubt, refer to the MongoDB installation guide and the rs.initiate command for further details.

  1. Download MongoDB 3.4 community server.
  2. Create a directory for the MongoDB data files (e.g., /tmp/mongo/).
  3. Start MongoDB (mongod or mongod.exe) with the following parameters:
    --dbpath /tmp/mongo/ --replSet rs1
    Note: rs1 is the default replication set name expected by ToroDB Stampede.

By now, you should have a running MongoDB listening on localhost port 27017 without access control. This allows the MongoDB shell as well as ToroDB Stampede to connect without any arguments.

To configure a single-node replica set (named rs1), start the MongoDB shell and run the following command in the just started MongoDB server:

      _id: "rs1",
      version: 1,
      members: [
            _id: 0,
            host: ""


Follow the instructions on the PostgreSQL downloads page to download and install PostgreSQL.

Once PostgreSQL is running create a user and database for ToroDB Stempede:

  1. Use PostgreSQL's createuser to create the user torodb.
    On Linux, this can be done with the following command:
    sudo -u postgres createuser -S -R -D -P --interactive torodb
    You will be asked for a password, which you'll need to tell ToroDB Stampede in a moment.
  2. Create database torod with owner torodb.
    On Linux, this can be done with the following command:
    sudo -u postgres createdb -O torodb torod
  3. Verify the connectivity.
    On Linux, this can be done with the following command:
    psql -U torodb torod

ToroDB Stampede

Download the latest ToroDB Stampede binary distribution from the downloads page and start it with the --ask-for-password option.

On Linux, this can be done with the following commands:

wget "https://www.torodb.com/download/torodb-stampede-latest.tar.bz2"

tar xjf torodb-stampede-*.tar.bz2

torodb-stampede-*/bin/torodb-stampede --ask-for-password

ToroDB Stampede will ask for the password of the torodb PostgreSQL user you just created.

By now, you should have running sandbox environment. Changes done in MongoDB are replicated to PostgreSQL and stored in the relational schema. The following sections demos ToroDB Stampede by uploading test data into MongoDB and runing a very simple query against this data in the PostgreSQL database.

Uploading Test Data

You can import the "primer dataset" into MongoDB as described in the MongoDB manual:

On Linux, the following commands will do the trick:

wget https://www.torodb.com/download/primer-dataset.json

mongoimport --db test --collection restaurants primer-dataset.json

Note that the MongoDB database name (test) is mapped to a PostgreSQL schema. You can either connect with your favourite GUI to PostgreSQL or use psql on the command line:

psql -U torodb torod

> set schema 'test'

To view the table created by ToroDB Stampede, use the \d command in psql:

torod=> \d
                  List of relations
 Schema |           Name            | Type  | Owner
 test   | restaurants               | table | torodb
 test   | restaurants_address       | table | torodb
 test   | restaurants_address_coord | table | torodb
 test   | restaurants_grades        | table | torodb
(4 rows)

The chapter Relational Schema explains how JSON documents are mapped to tables.

Example Query

To list each ZIP code with the number of restaurants in order of decending number of restaurants:

select zipcode_s, count(*)
  from restaurants_address
 group by zipcode_s
 order by count(*) desc;
 count | zipcode_s
   686 | 10003
   675 | 10019
   611 | 10036
   520 | 10001
   485 | 10022

The equivalent MongoDB query would be:

        { $group: {"_id": "$address.zipcode", count:{ $sum:1} } },
        { $sort:  { count: -1 } }
{ "_id" : "10003", "count" : 686 }
{ "_id" : "10019", "count" : 675 }
{ "_id" : "10036", "count" : 611 }
{ "_id" : "10001", "count" : 520 }
{ "_id" : "10022", "count" : 485 }