Apache Kafka is a popular distributed streaming data platform. A Kafka cluster stores streams of records (messages) in categories called topics. It is the architectural backbone for integrating streaming data with a Data Lake, Microservices and Stream Processing. Data sources flowing into Kafka are often native data streams such as social media streams, telemetry data, financial transactions and many others. But these data stream only contain part of the information. A lot of data necessary in stream processing is stored in traditional systems backed by relational databases. To implement new and modern, real-time solutions, an up-to-date view of that information is needed. So how do we make sure that information can flow between the RDBMS and Kafka, so that changes are available in Kafka as soon as possible in near-real-time? This session will present different approaches for integrating relational databases with Kafka, such as Kafka Connect, Oracle GoldenGate and bridging Kafka with Oracle Advanced Queuing (AQ).

1. BASEL | BERN | BRUGG | BUCHAREST | COPENHAGEN | DÜSSELDORF | FRANKFURT A.M. | FREIBURG I.BR.
GENEVA | HAMBURG | LAUSANNE | MANNHEIM | MUNICH | STUTTGART | VIENNA | ZURICH
http://guidoschmutz@wordpress.com@gschmutz
Solutions for bi-directional integration
between Oracle RDBMS & Apache Kafka
Guido Schmutz
DOAG Konferenz 2019

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

3. BASEL | BERN | BRUGG | BUKAREST | DÜSSELDORF | FRANKFURT A.M. | FREIBURG I.BR. | GENF
HAMBURG | KOPENHAGEN | LAUSANNE | MANNHEIM | MÜNCHEN | STUTTGART | WIEN | ZÜRICH
Guido
Working at Trivadis for more than 22 years
Consultant, Trainer, Platform Architect for Java,
Oracle, SOA and Big Data / Fast Data
Oracle Groundbreaker Ambassador & Oracle ACE
Director
@gschmutz guidoschmutz.wordpress.com
171st
edition

5. Introduction

6. 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

7. Microservices / Modern Applications
Integrate with Traditional System
M3M2
ACL
Event
Hub
M1
ACL
• 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!
Traditional
App

8. Use Case
Customer Microservice
{ }
Customer API CustomerCustomer Logic
Order Processing System
{ }
Order API OrderOrder Logic
REST
REST
Event Hub
Customer
Mat View
Order
Customer
(compacted)
Notification Microservice
Notification Logic
Flat Aggregate
Low Latency High Latency
DB Dataflow
Message
Latency
ACL
Open Source CommercialLicense
“Modern Apps”Traditional Apps (Legacy)

9. 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
Open Source CommercialLicense

10. Properties - Latency
Traditional System Event
Hub
Data
Flow
RDBMS
latency
latency
Flat Aggregate
Low Latency High Latency
DB Dataflow
Message
Latency
ACL
Open Source CommercialLicense

11. 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
Open Source CommercialLicense
Examples:
• View Layer
• Storage Procedure
• JSON Support in DB
• …
Examples:
• StreamSets
• Kafka Connect
• Kafka Streams / KSQL
• …
Database Dataflow

12. Blueprints Oracle RDBMS =>
Apache Kafka

13. 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
Mat View
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 Que with bridge to Event Hub
DB_K-1
DB_K-2
DB_K-3
DB_K-4
DB_K-5

14. 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
Flat Aggregate
Low Latency High Latency
DB Dataflow
Message
Latency
ACL
Open Source CommercialLicense

15. 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
Open Source CommercialLicense
DB-K_1: Polling of RDBMS table/view
Kafka Connect with JDBC Source Connector

16. Kafka Connect & JDBC Connector
• Many connectors available
• Single Message Transforms (SMT)
• declarative style, simple data flows
• framework is part of Apache Kafka

17. 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"
}
}'

18. 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
Flat Aggregate
Low Latency High Latency
DB Dataflow
Message
Latency
ACL
Open Source CommercialLicense

19. 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
Open Source CommercialLicense
Alternatives:
StreamSets Data Collector
Attunity
Debezium
…

20. 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
Flat Aggregate
Low Latency High Latency
DB Dataflow
Message
Latency
ACL
Open Source CommercialLicense

21. 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
Open Source CommercialLicense

22. Oracle REST Data Services (ORDS)
• makes it easy to develop modern REST interfaces for relational data in the
Oracle Database and the Oracle Database 18c JSON Document Store
• ORDS maps HTTP(S) verbs (GET, POST, PUT, DELETE, etc.) to database
transactions and returns any results formatted using JSON
• Java middle tier application on WebLogic, Tomcat, Docker, Standalone (for
development)

23. 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);

24. 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 =>
'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'')'

25. StreamSets Data Collector
• GUI-based, drag-and
drop Data Flow Pipelines
• Both stream and batch
processing
• custom sources, sinks,
processors
• Monitoring and Error
Detection

26. DB-K_4: Produce to Event Hub from RDBMS
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
Open Source CommercialLicense

27. 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
Open Source CommercialLicense
DB-K_4: Produce to Event Hub from RDBMS
Native Kafka Producer using Java in DB
Does not feel right!

28. 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
Open Source CommercialLicense
DB-K_4: Produce to Event Hub from RDBMS
Invoke REST Proxy from PL/SQL
Invoking a REST Service
from DB not well-supported

29. 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 Big Data SQL
Coming soon …
DB-K_4: Produce to Event Hub from RDBMS
Oracle Big Data SQL integrates with Kafka
Flat Aggregate
Low Latency High Latency
DB Dataflow
Message
Latency
ACL
Open Source CommercialLicense

30. 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
Flat Aggregate
Low Latency High Latency
DB Dataflow
Message
Latency
ACL
Open Source CommercialLicense

31. 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
Open Source CommercialLicense

32. 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;
/

33. 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)

34. 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
Open Source CommercialLicense
AQ (Kafka API)
Oracle works on a Kafka API
for Advanced Queuing

35. Blueprints Apache Kafka =>
Oracle RDBMS

36. Blueprints Apache Kafka => Oracle RDBMS (K-DB)
Customer Microservice
{ }
Customer API CustomerCustomer Logic
Order Processing System
{ }
Order API OrderOrder Logic
REST
REST
Event Hub
Customer
Mat View
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
K_DB-1
K_DB-2
K_DB-3
K_DB-4

37. 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
Flat Aggregate
Low Latency High Latency
DB Dataflow
Message
Latency
ACL
Open Source CommercialLicense

38. 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
Open Source CommercialLicense
K-DB_1: Write to RDBMS table/view
Kafka Connect and JDBC Sink Connector

39. 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
Flat Aggregate
Low Latency High Latency
DB Dataflow
Message
Latency
ACL
Open Source CommercialLicense

40. 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
Open Source CommercialLicense
K-DB_2: Write over RDBMS API
Kafka Connect invokes Oracle Rest Data Service

41. 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( ... )

42. 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
Flat Aggregate
Low Latency High Latency
DB Dataflow
Message
Latency
ACL
Open Source CommercialLicense

43. 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 Big Data SQL
Coming soon…
K-DB_3: Consume from Event Hub
Oracle Big Data SQL exposes topic as table
Flat Aggregate
Low Latency High Latency
DB Dataflow
Message
Latency
ACL
Open Source CommercialLicense

44. 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
Flat Aggregate
Low Latency High Latency
DB Dataflow
Message
Latency
ACL
Open Source CommercialLicense

45. 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
Open Source CommercialLicense

46. 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 works 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
Open Source CommercialLicense

47. Summary

48. Summary
Customer Microservice
{ }
Customer API CustomerCustomer Logic
Order Processing System
{ }
Order API OrderOrder Logic
REST
REST
Event Hub
Customer
Mat View
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
K_DB-1
K_DB-2
K_DB-3
K_DB-4
DB_K-1
DB_K-2
DB_K-3
DB_K-4
DB_K-5
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

49. 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

50. 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