Categories: EAIESBJava / JEE

JBoss OneDayTalk 2013: “NoSQL Integration with Apache Camel – MongoDB, CouchDB, Neo4j, Cassandra, HBase, Hazelcast, Riak, etc.”

JBoss OneDayTalk is a great annual event around open source development. I have done a talk about “NoSQL Integration with Apache Camel”. This blog post shows you the updated slide deck of this talk.

Abstract

SQL cannot solve several problems emerging with big data. A distributed, fault-tolerant architecture is necessary. NoSQL comes to the rescue, but therefore it does not use SQL as its query language or give full ACID guarantees. Thus, in the future you will have to learn new concepts and integrate these NoSQL databases as you integrate SQL databasestoday. The open source integration framework Apache Camel is already prepared for this challenging task.

Apache Camel implements the well-known Enteprise Integration Patterns (EIP) and therefore offers a standardized, domain-specific language to integrate applications and clouds. It can be used in almost every integration project within the JVM environment. All integration projects can be realized in a consistent way without redundant boilerplate code.

This session demonstrates the elegance of Apache Camel for NoSQL integration. Several examples are shown for all different concepts by integrating NoSQL databases from CouchDB (Document Store), HBase (Column-oriented), Neo4j (Graph), Amazon Web Services (Key Value Store), and others.

If the required NoSQL database is not supported by Apache Camel, you can easily create your own Camel component with very low effort. This procedure is explained at the end of the session.

Slides

You are currently viewing a placeholder content from Default. To access the actual content, click the button below. Please note that doing so will share data with third-party providers.

More Information

Kai Waehner

bridging the gap between technical innovation and business value for real-time data streaming and applied AI.

Recent Posts

Complex Event Processing (CEP) with Apache Flink: What It Is and When (Not) to Use It

Complex Event Processing is the most underused capability in Apache Flink. It detects meaningful event…

4 days ago

MCP vs. REST/HTTP API vs. Kafka: The Architect’s Guide to Agentic AI Integration

MCP, REST/HTTP APIs, and Apache Kafka are not alternatives. They solve different problems at different…

1 week ago

Enterprise Agentic AI Landscape 2026: Trust, Flexibility, and Vendor Lock-in

The Enterprise Agentic AI Landscape 2026 maps every major AI vendor across two dimensions that…

2 weeks ago

The Trinity of Modern Data Architecture: Process Intelligence, Event-Driven Integration, and Trusted Agentic AI

Agentic AI without governed processes is fast but ungoverned. Event-driven integration without process intelligence moves…

2 weeks ago

dbt Meets Apache Flink: One Workflow for Data Engineers on Snowflake, BigQuery, Databricks, and Confluent

Two toolchains, two skill sets, two CI/CD pipelines — that has been the reality for…

3 weeks ago

The Shift Left Architecture 2.0: Operational, Analytical and AI Interfaces for Real-Time Data Products

The Shift Left Architecture moves data integration logic into an event-driven architecture where governed data…

4 weeks ago