The Stream Reactor components are built around The Confluent Platform. They rely on the Kafka Brokers, Zookeepers and optionally the Schema Registry provided by this distribution.

The following releases are available:

Kafka Version Confluent Version Stream reactor version 3.2 0.2.5 3.1 0.2.4 3.0.1 0.2.3 3.0.1 0.2.2
Connector Versions
Azure DocumentDB 1.9.5
BlockChain Not applicable
Bloomberg blpapi-3.8.8-2
Cassandra Driver 3.0.0, Server 3.0.9
CoAP Californium 2.0.0-M2
Druid Tranquility 0.7.4
Elastic Elastic 2.2.0, Elastic4s 2.3.0
FTP commons-net 0.5
HazelCast HazelCast 3.6.0
HBase HBase Server 1.2.0, HBase Client 1.2.0
InfluxDB InfluxDB 2.3
JMS javax.jms 1.1-rev-1, active-mq-code 1.26.0
Kudu Kudu Client 0.9.0
MongoDB MongoDB 3.3.0
MQTT Mqtt 1.1.0
Redis Redis 2.8.1
ReThinkDB ReThinkDB 2.3.3
VoltDB VoltDB 6.4
Yahoo yahoofinance-api 1.3.0

Install Confluent

Confluent can be downloaded for here

#make confluent home folder
➜  mkdir confluent

#download confluent
➜  wget

#extract archive to confluent folder
➜  tar -xvf confluent-3.2.0-2.11.tar.gz -C confluent

#setup variablesexport CONFLUENT_HOME=~/confluent/confluent-3.2.0

Start the Confluent platform.

#Start the confluent platform, we need kafka, zookeeper and the schema registry
bin/zookeeper-server-start etc/kafka/ &
sleep 10 && bin/kafka-server-start etc/kafka/ &
sleep 10 && bin/schema-registry-start etc/schema-registry/ &

Stream Reactor Install

Download the latest release from here.

Unpack the archive:

#Stream reactor release 0.2.5
mkdir stream-reactor
tar xvf stream-reactor-0.2.5-3.2.0.tar.gz -C stream-reactor

Within the unpacked directory you will find the following structure:

|-- bin
|   |--
|   |--
|   |-- sr-cli-linux
|   |-- sr-cli-osx
|   |--
|   `--
|-- conf
|   |--
|   |--
|   |--
|   |--
|   |--
|   |--
|   |--
|   |--
|   |--
|   |--
|   |--
|   |--
|   |--
|   |--
|   |--
|   |--
|   |--
|   |--
|   |--
|   |--
|   |--
|   |--
|   |--
|   |--
|   `--
`-- libs
    |-- kafka-connect-azure-documentdb-0.2.5-3.2.0-all.jar
    |-- kafka-connect-blockchain-0.2.5-3.2.0-all.jar
    |-- kafka-connect-bloomberg-0.2.5-3.2.0-all.jar
    |-- kafka-connect-cassandra-0.2.5-3.2.0-all.jar
    |-- kafka-connect-cli-1.0-all.jar
    |-- kafka-connect-coap-0.2.5-3.2.0-all.jar
    |-- kafka-connect-druid-0.2.5-3.2.0-all.jar
    |-- kafka-connect-elastic-0.2.5-3.2.0-all.jar
    |-- kafka-connect-ftp-0.2.5-3.2.0-all.jar
    |-- kafka-connect-hazelcast-0.2.5-3.2.0-all.jar
    |-- kafka-connect-hbase-0.2.5-3.2.0-all.jar
    |-- kafka-connect-influxdb-0.2.5-3.2.0-all.jar
    |-- kafka-connect-jms-0.2.5-3.2.0-all.jar
    |-- kafka-connect-kudu-0.2.5-3.2.0-all.jar
    |-- kafka-connect-mongodb-0.2.5-3.2.0-all.jar
    |-- kafka-connect-mqtt-0.2.5-3.2.0-all.jar
    |-- kafka-connect-redis-0.2.5-3.2.0-all.jar
    |-- kafka-connect-rethink-0.2.5-3.2.0-all.jar
    |-- kafka-connect-voltdb-0.2.5-3.2.0-all.jar
    `-- kafka-connect-yahoo-0.2.5-3.2.0-all.jar

The libs folder contains all the Stream Reactor Connector jars.

The bin folder contains the script. This loads all the Stream Reactors jars onto the CLASSPATH and starts Kafka Connect in distributed mode. The Confluent Platform, Zookeeper, Kafka and the Schema Registry must be started first.

Docker Install

All the Stream Reactor Connectors, Confluent and UI’s for Connect, Schema Registry and topic browsing are available in Dockers. The Docker images are available in DockerHub and maintained by our partner Landoop

Pull the latest images:

docker pull landoop/fast-data-dev
docker pull landoop/fast-data-dev-connect-cluster

docker pull landoop/kafka-topics-ui
docker pull landoop/schema-registry-ui

Individual docker images are available at DataMountaineers DockerHub. We base our Docker images of Confluents base connector image. This contains a script that uses the environment variables starting with CONNECT_ to create the Kafka Connect Worker property files. We added a second script that uses the environment variables starting with CONNECTOR_ to create a properties files for the actual connector we want to start.

Set the CONNECT_ and CONNECTOR_ environment variables accordingly when running the images.

Release Notes


  • Adding Azure DocumentDb Sink
  • Adding UPSERT to Elastic Search
  • Cassandra improvements withunwrap
  • Upgrade to Kudu 1.0 and CLI 1.0
  • Add ingest_time to CoAP Source
  • Support Confluent 3.2 and Kafka 0.10.2.
  • Added Azure DocumentDB.
  • Added JMS Source.
  • Added Schemaless Json and Json with schema support to JMS Sink.
  • InfluxDB bug fixes for tags and field selection.
  • Support for Cassandra data type of timestamp in the Cassandra Source for timestamp tracking.

0.2.4 (26 Jan 2017)

  • Added FTP and HTTP Source.
  • Added InfluxDB tag support. KCQL: INSERT INTO target dimension SELECT * FROM influx-topic WITHTIMESTAMP sys_time() WITHTAG(field1, CONSTANT_KEY1=CONSTANT_VALUE1, field2,CONSTANT_KEY2=CONSTANT_VALUE1)
  • Added InfluxDb consistency level. Default is ALL. Use connect.influx.consistency.level to set it to ONE/QUORUM/ALL/ANY.
  • InfluxDb connect.influx.sink.route.query was renamed to connect.influx.sink.kcql.
  • Added support for multiple contact points in Cassandra.

0.2.3 (5 Jan 2017)

  • Added CoAP Source and Sink.
  • Added MongoDB Sink.
  • Added MQTT Source.
  • Hazelcast support for ring buffers, maps, sets, lists and cache.
  • Redis support for Sorted Sets.
  • Added start scripts.
  • Added Kafka Connect and Schema Registry CLI.
  • Kafka Connect CLI now supports pause/restart/resume; checking connectors on the classpath and validating configuration of connectors.
  • Support for Struct, Schema.STRING and Json with schema in the Cassandra, ReThinkDB, InfluxDB and MongoDB sinks.
  • Rename export.query.route to sink.kcql.
  • Rename import.query.route to source.kcql.
  • Upgrade to KCQL 0.9.5 - Add support for STOREAS so specify target sink types, e.g. Redis Sorted Sets, Hazelcast map, queues, ringbuffers.

Fast Data Dev

This is Docker image for development.

If you need

  1. Kafka Broker
  2. ZooKeeper
  3. Schema Registry
  4. Kafka REST Proxy
  5. Kafka Connect Distributed
  6. Certified DataMountaineer Connectors (ElasticSearch, Cassandra, Redis ..)
  7. Landoop’s Fast Data Web UIs : schema-registry , kafka-topics , kafka-connect and
  8. Embedded integration tests with examples

Run with:

docker run --rm -it --net=host landoop/fast-data-dev

On Mac OSX run:

docker run --rm -it \
       -p 2181:2181 -p 3030:3030 -p 8081:8081 \
       -p 8082:8082 -p 8083:8083 -p 9092:9092 \
       -e ADV_HOST= \

That’s it. Your Broker is at localhost:9092, your Kafka REST Proxy at localhost:8082, your Schema Registry at localhost:8081, your Connect Distributed at localhost:8083, your ZooKeeper at localhost:2181 and at http://localhost:3030 you will find Landoop’s Web UIs for Kafka Topics and Schema Registry, as well as a Coyote test report.

Fast Data Dev Connect

This docker is targeted to more advanced users and is a special case since it doesn’t set-up a Kafka cluster, instead it expects to find a Kafka Cluster with Schema Registry up and running.

The developer can then use this docker image to setup a connect-distributed cluster by just spawning a couple containers.

docker run -d --net=host \
       -e ID=01 \
       -e BS=broker1:9092,broker2:9092 \
       -e ZK=zk1:2181,zk2:2181 \
       -e SC=http://schema-registry:8081 \
       -e HOST=<IP OR FQDN> \

Things to look out for in configuration options:

  1. It is important to give a full URL (including schema —http://) for schema registry.

2. ID should be unique to the Connect cluster you setup, for current and old instances. This is because Connect stores data in Brokers and Schema Registry. Thus even if you destroyed a Connect cluster, its data remain in your Kafka setup.

3. HOST should be set to an IP address or domain name that other connect instances and clients can use to reach the current instance. We chose not to try to autodetect this IP because such a feat would fail more often than not. Good choices are your local network ip (e.g if you work inside a local network, your public ip (if you have one and want to use it) or a domain name that is resolvable by all the hosts you will use to talk to Connect.

If you don’t want to run with –net=host you have to expose Connect’s port which at default settings is 8083. There a PORT option, that allows you to set Connect’s port explicitly if you can’t use the default 8083. Please remember that it is important to expose Connect’s port on the same port at the host. This is a choice we had to make for simplicity’s sake.

docker run -d \
       -e ID=01 \
       -e BS=broker1:9092,broker2:9092 \
       -e ZK=zk1:2181,zk2:2181 \
       -e SC=http://schema-registry:8081 \
       -e HOST=<IP OR FQDN> \
       -e PORT=8085 \
       -p 8085:8085 \


The container does not exit with CTRL+C. This is because we chose to pass control directly to Connect, so you check your logs via docker logs. You can stop it or kill it from another terminal.

Whilst the PORT variable sets the rest.port, the HOST variable sets the advertised host. This is the hostname that Connect will send to other Connect instances. By default Connect listens to all interfaces, so you don’t have to worry as long as other instances can reach each instance via the advertised host.

Latest Test Results

To see the latest tests for the Connectors, in a docker, please visit Landoop’s test github here Test results can be found here.

An example for BlockChain is: