Apache Kafka is a popular distributed streaming data platform and more and more is the architectural backbone for integrating streaming data with a Data Lake, Microservices and Stream Processing. A lot of data necessary in stream processing is stored in traditional systems backed by relational databases. This session will present different approaches for integrating relational databases with Kafka, such as Kafka Connect, Oracle GoldenGate, ORDS APIs and bridging Kafka with Oracle AQ.

1. http://guidoschmutz@wordpress.com@gschmutz
Solutions for bi-directional integration
between Oracle RDBMS & Apache Kafka
Guido Schmutz

2. virtual SOUG Day
sponsored by
Platinum Sponsors Gold Sponsors

3. Guido
Working at Trivadis for more than 23 years
Consultant, Trainer, Platform Architect for Java,
Oracle, SOA and Big Data / Fast Data
Oracle Groundbreaker Ambassador & Oracle ACE
Director
@gschmutz guidoschmutz.wordpress.com
191st
edition

5. Agenda
1. Motivation & Introduction
2. Blueprints Oracle RDBMS => Apache Kafka
3. Blueprints Apache Kafka => Oracle RDBMS
4. Summary

6. Motivation & Introduction

7. Microservices / Modern Applications
• Highly decoupled
• Independently deployable
• Bounded Context/Aggregate (DDD)
• Responsible for their data
• Favour asynchronous, event-driven
interaction over synchronous
• Smart Endpoints and Dump Pipes
• Use Anti-Corruption Layer (ACL) if no fit!
M3M2
ACL
Event
Hub
M1

8. Microservices / Modern Applications
Integrate with Traditional System
M3M2
ACL
Event
Hub
M1
ACL
Traditional
App
• Highly decoupled
• Independently deployable
• Bounded Context/Aggregate (DDD)
• Responsible for their data
• Favour asynchronous, event-driven
interaction over synchronous
• Smart Endpoints and Dump Pipes
• Use Anti-Corruption Layer (ACL) if no fit!

9. Apache Kafka – A Streaming Platform
Kafka Cluster
Consumer 1 Consume 2
Broker 1 Broker 2 Broker 3
Zookeeper
Ensemble
ZK 1 ZK 2ZK 3
Schema
Registry
Service 1
Management
Control Center
Kafka Manager
KAdmin
Producer 1 Producer 2
kafkacat
Data Retention:
• Never
• Time (TTL) or Size-based
• Log-Compacted based
Producer3Producer3
ConsumerConsumer 3
Consumer Pulls (Polling Consumer)
Producer Pushes (Polling Consumer)
record
record
record
recordrecord

10. Order Processing System
Use Case
Customer Microservice
{ }
Customer API CustomerCustomer Logic
{ }
Order API OrderOrder Logic
REST
REST
Event Hub
Order
Customer
(compacted)
Notification Microservice
Notification Logic
“Modern Apps”Traditional Apps (Legacy)
Flat Aggregate
Low Latency High Latency
DB Dataflow
Message
Latency
ACL
Included AdditionalLicense
RDBMS as
“Producer”
RDBMS as
“Consumer”
Customer

11. MessageMessageMessageMessage
MessageMessage
Properties - Message
Message Message
A1 A2 A3
Message
B1 B2 B3 B4
A1 A2 A3 B []
B1 B2 B3 B4
Table A
A1
A2
A3
Table B
B1
B2
B3
B4
FlatDB Model Aggregate
Flat Aggregate
Low Latency High Latency
DB Dataflow
Message
Latency
ACL
Included AdditionalLicense

12. Properties - Latency
Traditional System Event
Hub
Data
Flow
RDBMS
latency
latency
Flat Aggregate
Low Latency High Latency
DB Dataflow
Message
Latency
ACL
Included AdditionalLicense

13. Properties – Anti-Corruption Layer (ACL)
Traditional System Event
Hub
Data
Flow
RDBMS
Traditional System Event
Hub
Data
Flow
RDBMS
ACL
ACL
Flat Aggregate
Low Latency High Latency
DB Dataflow
Message
Latency
ACL
Included AdditionalLicense
Examples:
• View Layer
• Storage Procedure
• JSON Support in DB
• …
Examples:
• StreamSets
• Kafka Connect
• Kafka Streams / KSQL
• …
Database Dataflow

14. Properties – License
• Included
• either part of Oracle RDMBS license
• or part of Kafka open source or Confluent Enterprise Platform
• or additional free software (mostly open source) component
• Additional Commercial Licenses
• an additional component involving license costs
Flat Aggregate
Low Latency High Latency
DB Dataflow
Message
Latency
ACL
Included AdditionalLicense

15. Blueprints Oracle RDBMS =>
Apache Kafka

16. Blueprints Oracle RDBMS => Apache Kafka (DB-K)
Customer Microservice
{ }
Customer API CustomerCustomer Logic
Order Processing System
{ }
Order API OrderOrder Logic
REST
REST
Event Hub
Customer
Order
(compacted)
Customer
(compacted)
Notification Microservice
Notification Logic
Schema
Registry
DB-K_1: Polling of RDBMS table/view
DB-K_2: Change Data Capture (CDC) on RDBMS
DB-K_3: Polling of RDBMS API
DB-K_4: Produce to Event Hub from RDBMS
DB-K_5: RDBMS Queue with bridge to Event Hub
https://github.com/gschmutz/various-demos/tree/master/bidirectional-integration-oracle-kafka

17. DB-K_1: Polling of RDBMS table/view
Event
Hub
Stream Data
Integration
API
Applications / Data Sources
Data FlowRDBMS
Application
Logic
Stream Data
Integration & Analytics
Stream
Analytics
Data Flow

18. Event
Hub
Stream Data
Integration
API
Applications / Data Sources
Data FlowRDBMS
Application
Logic
Stream Data
Integration & Analytics
Stream
Analytics
Data Flow
Flat Aggregate
Low Latency High Latency
DB Dataflow
Message
Latency
ACL
Included AdditionalLicense
DB-K_1: Polling of RDBMS table/view
Kafka Connect with JDBC Source Connector
JDBC Connector part of Confluent Open Source Platform

19. Kafka Connect & JDBC Connector
• Many connectors available
• Single Message Transforms (SMT)
• declarative style, simple data flows
• framework is part of Apache Kafka
https://www.confluent.io/hub

20. DB-K_1 – Configure JDBC Connector
#!/bin/bash
curl -X "POST" "http://192.168.69.138:8083/connectors"
-H "Content-Type: application/json"
-d $'{
"name": "jdbc-driver-source",
"config": {
"connector.class": "JdbcSourceConnector",
"connection.url":"jdbc:oracle:thin//oracle-db:1521/XEPDB1",
"mode": "timestamp",
"timestamp.column.name":”modified_at",
"table.whitelist":”order",
"validate.non.null":"false",
"topic.prefix":”orderprocessing_",
"key.converter":"org.apache.kafka.connect.json.JsonConverter",
"key.converter.schemas.enable": "false",
"value.converter":"org.apache.kafka.connect.json.JsonConverter",
"value.converter.schemas.enable": "false",
"name": "jdbc-driver-source",
"transforms":"createKey,extractInt",
"transforms.createKey.type":"org.apache.kafka.connect.transforms.ValueToKey",
"transforms.createKey.fields":"id",
"transforms.extractInt.type":"org.apache.kafka.connect.transforms.ExtractField$Key",
"transforms.extractInt.field":"id"
}
}'

21. DB-K_2: Change Data Capture (CDC) on RDBMS
Stream Data
Integration & Analytics
Stream
Analytics
Event
Hub
Stream Data
Integration
API
Data Flow
Application / Data Sources
Data Flow
Application
Logic
RDBMS
Redo Log
REST to
Event Hub

22. Stream Data
Integration & Analytics
Stream
Analytics
Event
Hub
Stream Data
Integration
API
Data Flow
Application / Data Sources
Data Flow
Application
Logic
RDBMS
Redo Log
REST to
Event Hub
Rest Proxy
DB-K_2: Change Data Capture (CDC) on RDBMS
Using Oracle GoldenGate
Flat Aggregate
Low Latency High Latency
DB Dataflow
Message
Latency
ACL
Included AdditionalLicense
Alternatives:
StreamSets Data Collector
Qlik Replicate
Debezium
…

23. DB-K_3: Polling of RDBMS API
Event
Hub
Stream Data
Integration
API
Applications / Data Sources
Data Flow
RDBMS
Application
Logic
API
Stream Data
Integration & Analytics
Stream
Analytics
Data Flow

24. Event
Hub
Stream Data
Integration
API
Applications / Data Sources
Data Flow
RDBMS
Application
Logic
API
Stream Data
Integration & Analytics
Stream
Analytics
Data Flow
DB-K_3: Polling of RDBMS API
StreamSets invokes Oracle Rest Data Service
Flat Aggregate
Low Latency High Latency
DB Dataflow
Message
Latency
ACL
Included AdditionalLicense Oracle Rest Data Service is part of Oracle RDBMS, StreamSets is Open Source
Alternatives:
NiFi
KafkaConnect
…

25. Oracle REST Data Services (ORDS)
• ORDS maps HTTP(S) verbs (GET, POST, PUT, DELETE, etc.) to database transactions and
returns any results formatted using JSON
• simplifies development of modern REST interfaces on top of Oracle Database and Oracle
Database 18c JSON Document Store
• deployment on WebLogic, Tomcat, Docker, Standalone (for development)
https://www.oracle.com/database/technologies/appdev/rest.html

26. DB-K_3 – Setup ORDS (I)
ORDS.ENABLE_SCHEMA(
p_enabled => TRUE,
p_schema => 'ORDER_PROCESSING',
p_url_mapping_type => 'BASE_PATH',
p_url_mapping_pattern => 'order_processing',
p_auto_rest_auth => FALSE);
ORDS.DEFINE_MODULE(
p_module_name => 'order_processing',
p_base_path => '/orders/',
p_items_per_page => 25,
p_status => 'PUBLISHED',
p_comments => NULL);
ORDS.DEFINE_TEMPLATE(
p_module_name => 'order_processing',
p_pattern => 'changes/:offset',
p_priority => 0,
p_etag_type => 'HASH',
p_etag_query => NULL,
p_comments => NULL);

27. DB-K_3 – Setup ORDS (II)
ORDS.DEFINE_HANDLER(
p_module_name => 'order_processing',
p_pattern => 'changes/:offset',
p_method => 'GET',
p_source_type => 'resource/lob',
p_items_per_page => 25,
p_source => q'[
'SELECT 'application/json', json_object('orderId' VALUE po.id,
'orderDate' VALUE po.order_date,
'orderMode' VALUE po.order_mode,
'customer' VALUE
json_object('firstName' VALUE cu.first_name,
'lastName' VALUE cu.last_name
'emailAddress' VALUE cu.email),
'lineItems' VALUE (SELECT json_arrayagg(
json_object('ItemNumber' VALUE li.id,
'Product' VALUE
json_object('id' VALUE li.product_id,
'name' VALUE li.product_name,
'unitPrice' VALUE li.unit_price),
'quantity' VALUE li.quantity))
FROM order_item_t li WHERE po.id = li.order_id),
'offset' VALUE TO_CHAR(po.modified_at, 'YYYYMMDDHH24MISS'))
FROM order_t po LEFT JOIN customer_t cu ON (po.customer_id = cu.id)
WHERE po.modified_at > TO_DATE(:offset, 'YYYYMMDDHH24MISS')]'

28. StreamSets Data Collector
• GUI-based, drag-and drop Data
Flow Pipelines
• Both stream and batch
processing
• custom sources, sinks,
processors
• Monitoring and Error Detection
https://streamsets.com/products/sdc

29. DB-K_4: Produce to Event Hub from Kafka
Event
Hub
Stream Data
Integration
API
Applications / Data Sources
RDBMS
Application
Logic
API
Stream Data
Integration & Analytics
Stream
Analytics
Data Flow
REST to
Event Hub

30. Event
Hub
Stream Data
Integration
API
Applications / Data Sources
RDBMS
Application
Logic
API
Stream Data
Integration & Analytics
Stream
Analytics
Data Flow
REST to
Event Hub
Flat Aggregate
Low Latency High Latency
DB Dataflow
Message
Latency
ACL
Included AdditionalLicense
DB-K_4: Produce to Event Hub from RDBMS
Native Kafka Producer using Java in DB
Doesn’t feel right!
1st Java in DB and 2nd “dual write” problem

31. Event
Hub
Stream Data
Integration
API
Applications / Data Sources
RDBMS
Application
Logic
API
Stream Data
Integration & Analytics
Stream
Analytics
Data Flow
REST to
Event Hub
Rest Proxy
?
Flat Aggregate
Low Latency High Latency
DB Dataflow
Message
Latency
ACL
Included AdditionalLicense
DB-K_4: Produce to Event Hub from RDBMS
Invoke REST Proxy from PL/SQL
1st Invoking a REST Service from DB not
well-supported & 2nd ”dual write” problem
Confluent REST Proxy is part of Confluent Open Source Platform

32. DB-K_5: RDBMS Queue with bridge to Event Hub
Stream Data
Integration & Analytics
Stream
Analytics
Event
Hub
Stream Data
Integration
API
Data Flow
Application / Data Sources
Data Flow
Application
Logic
RDBMS
Queue

33. DB-K_5: RDBMS Queue with bridge to Event Hub
Oracle Advanced Queuing & Kafka Connect JMS
Stream Data
Integration & Analytics
Stream
Analytics
Event
Hub
Stream Data
Integration
API
Data Flow
Application / Data Sources
Data Flow
Application
Logic
RDBMS
QueueAQ
Flat Aggregate
Low Latency High Latency
DB Dataflow
Message
Latency
ACL
Included AdditionalLicense Oracle Advanced Queuing is part of Oracle RDBMS

34. BEGIN
dbms_aqadm.create_queue_table (
queue_table => 'ORDER_QT',
queue_payload_type => 'SYS.AQ$_JMS_TEXT_MESSAGE',
sort_list => 'PRIORITY,ENQ_TIME',
multiple_consumers => FALSE,
message_grouping => dbms_aqadm.none
);
END;
/
DB-K_5 – Setup AQ and Kafka Connect (I)
BEGIN
dbms_aqadm.create_queue (
queue_name => 'ORDER_AQ',
queue_table => 'ORDER_QT',
max_retries => 1,
retry_delay => 2, -- seconds
retention_time => 60*60*24*7 -- 1w
);
END;
/
BEGIN
dbms_aqadm.start_queue(
queue_name => 'ORDER_AQ',
enqueue => TRUE,
dequeue => TRUE
);
END;
/

35. curl -X "POST" "$DOCKER_HOST_IP:8083/connectors"
-H "Content-Type: application/json"
--data '{
"name": "jms-source",
"config": {
"name": "jms-source",
"connector.class": "com.datamountaineer...JMSSourceConnector",
"connect.jms.initial.context.factory":
"oracle.jms.AQjmsInitialContextFactory",
"connect.jms.initial.context.extra.params":
"db_url=jdbc:oracle:thin:@//192.168.73.86:1521/XEPDB1,java.naming.security.princ
ipal=order_processing,java.naming.security.credentials=order_processing",
"tasks.max": "1",
"connect.jms.connection.factory": "ConnectionFactory",
"connect.jms.url": "jdbc:oracle:thin:@//192.168.73.86:1521/XEPDB1",
"connect.jms.kcql": "INSERT INTO order SELECT * FROM order_aq WITHTYPE QUEUE
WITHCONVERTER=`com.datamountaineer.streamreactor.connect.converters.source.JsonS
impleConverter`"
}
}'
DB-K_5 – Setup AQ and Kafka Connect (I)

36. DB-K_5: RDBMS Queue with bridge to Event Hub
Oracle AQ with Kafka API & MirrorMaker
Stream Data
Integration & Analytics
Stream
Analytics
Event
Hub
Stream Data
Integration
API
Data Flow
Application / Data Sources
Data Flow
Application
Logic
RDBMS
Queue
Flat Aggregate
Low Latency High Latency
DB Dataflow
Message
Latency
ACL
Included AdditionalLicense
AQ (Kafka API)
Oracle is working on a Kafka API
for Advanced Queuing

37. Blueprints Apache Kafka =>
Oracle RDBMS

38. Blueprints Apache Kafka => Oracle RDBMS (K-DB)
Customer Microservice
{ }
Customer API CustomerCustomer Logic
Order Processing System
{ }
Order API OrderOrder Logic
REST
REST
Event Hub
Order
(compacted)
Customer
(compacted)
Notification Microservice
Notification Logic
Schema
Registry
K-DB_1: Write to RDBMS table/view
K-DB_2: Write over RDBMS API
K-DB_3: Consume from Event Hub
K-DB_4: Event Hub with bridge to RDBMS Queue
Customer

39. K-DB_1: Write to RDBMS table/view
Event
Hub
Stream Data
Integration
API
Applications / Data Sources
Data FlowRDBMS
Application
Logic
Stream Data
Integration & Analytics
Stream
Analytics
Data Flow

40. Event
Hub
Stream Data
Integration
API
Applications / Data Sources
Data FlowRDBMS
Application
Logic
Stream Data
Integration & Analytics
Stream
Analytics
Data Flow
Flat Aggregate
Low Latency High Latency
DB Dataflow
Message
Latency
ACL
Included AdditionalLicense
K-DB_1: Write to RDBMS table/view
Kafka Connect and JDBC Sink Connector

41. K-DB_2: Write over RDBMS API
Event
Hub
Stream Data
Integration
API
Applications / Data Sources
Data Flow
RDBMS
Application
Logic
API
Stream Data
Integration & Analytics
Stream
Analytics
Data Flow

42. Event
Hub
Stream Data
Integration
API
Applications / Data Sources
Data Flow
RDBMS
Application
Logic
API
Stream Data
Integration & Analytics
Stream
Analytics
Data Flow
Flat Aggregate
Low Latency High Latency
DB Dataflow
Message
Latency
ACL
Included AdditionalLicense
K-DB_2: Write over RDBMS API
Kafka Connect invokes Oracle Rest Data Service
Oracle Rest Data Service is part of Oracle RDBMS, REST Connector is Open Source

43. DB-K_2 – Setup ORDS (I)
ORDS.DEFINE_HANDLER(
p_module_name => 'customer',
p_pattern => 'customer',
p_method => 'POST',
p_source_type => 'plsql/block',
p_items_per_page => 0,
p_source =>
'DECLARE
L_CU CLOB := :body_text;
BEGIN
INSERT INTO customer_t (id, first_name, last_name, title, notification_on, email, slack_handle,
twitter_handle)
SELECT * FROM json_table(L_CU, '$'
COLUMNS (
id NUMBER PATH '$.id',
first_name VARCHAR2 PATH '$.firstName',
last_name VARCHAR2 PATH '$.lastName',
title VARCHAR2 PATH '$.title',
notification_on VARCHAR2 PATH '$.notificationOn',
email VARCHAR2 PATH '$.email',
slack_handle VARCHAR2 PATH '$.slackHandle',
twitter_handle VARCHAR2 PATH '$.twitterHandle'
));
INSERT INTO address_t (customer_id, id, street, nr, city, postcode, country)
SELECT * FROM json_table( ... )

44. K-DB_3: Consume from Event Hub
Event
Hub
Stream Data
Integration
API
Applications / Data Sources
RDBMS
Application
Logic
API
Stream Data
Integration & Analytics
Stream
Analytics
Data Flow
REST to
Event Hub

45. Event
Hub
Stream Data
Integration
API
Applications / Data Sources
RDBMS
Application
Logic
API
Stream Data
Integration & Analytics
Stream
Analytics
Data Flow
REST to
Event Hub
Oracle SQL Access
to Kafka (OSaK)
K-DB_3: SQL SELECT from Event Hub
Oracle SQL Access to Kafka exposes topic as view
Flat Aggregate
Low Latency High Latency
DB Dataflow
Message
Latency
ACL
Included AdditionalLicense
Currently only supports JSON and delimited text
Blog: Integrating Data-in-Motion with Data-at-Rest using Oracle SQL Access to Kafka Views

46. K-DB_4: Event Hub with bridge to RDBMS queue
Stream Data
Integration & Analytics
Stream
Analytics
Event
Hub
Stream Data
Integration
API
Data Flow
Application / Data Sources
Data Flow
Application
Logic
RDBMS
Queue

47. Stream Data
Integration & Analytics
Stream
Analytics
Event
Hub
Stream Data
Integration
API
Data Flow
Application / Data Sources
Data Flow
Application
Logic
RDBMS
QueueAQ
K-DB_4: Event Hub with bridge to RDBMS queue
Oracle Advanced Queuing & Kafka Connect JMS
Flat Aggregate
Low Latency High Latency
DB Dataflow
Message
Latency
ACL
Included AdditionalLicense Oracle Advanced Queuing is part of Oracle RDBMS

48. Stream Data
Integration & Analytics
Stream
Analytics
Event
Hub
Stream Data
Integration
API
Data Flow
Application / Data Sources
Data Flow
Application
Logic
RDBMS
QueueAQ (Kafka API)
Oracle is working on a Kafka API
for Advanced Queuing
K-DB_4: Event Hub with bridge to RDBMS queue
Oracle AQ with Kafka API & MirrorMaker
Flat Aggregate
Low Latency High Latency
DB Dataflow
Message
Latency
ACL
Included AdditionalLicense

49. Summary

50. Summary
Customer Microservice
{ }
Customer API CustomerCustomer Logic
Order Processing System
{ }
Order API OrderOrder Logic
REST
REST
Event Hub
Order
(compacted)
Customer
(compacted)
Notification Microservice
Notification Logic
Schema
Registry
K-DB_1: Write to RDBMS table/view
K-DB_2: Write over RDBMS API
K-DB_3: Consume from Event Hub
K-DB_4: Event Hub with bridge to RDBMS Queue
https://github.com/gschmutz/various-demos/tree/master/bidirectional-integration-oracle-kafka
DB-K_1: Polling of RDBMS table/view
DB-K_2: Change Data Capture (CDC) on RDBMS
DB-K_3: Polling of RDBMS API
DB-K_4: Produce to Event Hub from RDBMS
DB-K_5: RDBMS Queue with bridge to Event Hub
Customer

51. Bulk Source
Ref Architecture
Data Platform
Service
Event
Stream
Bulk
Data
Flow
Event Source
Location
DB
Extract
File
Weather
DB
IoT
Data
Mobile
Apps
Social
File Import / SQL Import
Consumer
BI Apps
Data Science
Workbench
Enterprise
App
Enterprise Data
Warehouse
SQL / Search
SQL
“Native” Raw
RDBMS
“SQL” / Search
Service
Event
Hub
Hadoop ClusterdHadoop ClusterBig Data Platform
SQL
Export
Storage
Storage
Raw
Refined/
UsageOpt
Microservice Cluster
Stream Processing Cluster
Stream
Processor
Model /
State
Edge Node
Rules
Event Hub
Storage
Governance
Data Catalog
Rules
Engine
Parallel
Processing
Query
Engine
Microservice Data
{ }
API
Event
Stream
Event Stream
Modern Data Platform
Event Stream

52. Bulk Source
Ref Architecture
Data Platform
Service
Event
Stream
Bulk
Data
Flow
Event Source
Location
DB
Extract
File
Weather
DB
IoT
Data
Mobile
Apps
Social
File Import / SQL Import
Consumer
BI Apps
Data Science
Workbench
Enterprise
App
Enterprise Data
Warehouse
SQL / Search
SQL
“Native” Raw
RDBMS
“SQL” / Search
Service
sEvent
Hub
Hadoop ClusterdHadoop ClusterBig Data Platform
SQL
Export
Storage
Storage
Raw
Refined/
UsageOpt
Microservice Cluster
Stream Processing Cluster
Stream
Processor
Model /
State
Edge Node
Rules
Event Hub
Storage
Governance
Data Catalog
Rules
Engine
Parallel
Processing
Query
Engine
Microservice Data
{ }
API
Event
Stream
Event Stream
Modern Data Platform
Event Stream