Change Data Capture (CDC) | Nexla

Real-Time Data: Streaming and CDC for the Enterprise Data Layer

Capture database changes and process event streams in real time. Every source from Kafka topics, CDC feeds, webhooks, Kinesis streams, becomes a governed Nexset, ready for AI agents, analytics, and operational systems without custom integration code.

Real-time, Ready to use Data for Analytics, AI Agents, DWH

Every Stream Becomes a Governed Data Product

Connect Kafka, Kinesis, Pub/Sub, JMS, webhooks, and CDC sources. Nexla automatically converts topics, queues, and change feeds into Nexsets – governed virtual data products with schema, metadata, and access controls, without writing stream processing code.

Real-Time or Batch: One Data Product, Any Consumer

A Nexset from a streaming or CDC source is format, protocol, and speed-independent. Reuse the same data product in real-time for an AI agent via MCP, in near-real-time for an analytics dashboard, or in batch for a downstream warehouse load, without rebuilding the pipeline for each consumer.

No Stream Processing Complexity

Transform, enrich, and route real-time data using a no-code visual designer or AI prompts, without managing Kafka Streams, Flink, or custom consumer code. Nexla handles schema evolution, dead-letter queues, retries, and monitoring automatically.

Connect Any Real-Time Source

Nexla connects to streaming platforms, CDC sources, and webhook endpoints out of the box. Supported sources include:

Every Source Becomes a Governed Nexset

When Nexla connects to a streaming or CDC source, it automatically detects schema, extracts metadata, and creates a Nexset – a governed virtual data product. Nexsets are independent of the underlying protocol and speed. A Nexset from a Kafka topic looks the same to a downstream consumer as one from a CDC feed or a batch file.

Capture Database Changes the Moment They Happen

Nexla captures row-level changes from relational databases, data warehouses, and legacy systems as they occur and delivers them downstream in real time. Schema changes at the source are detected automatically. Nexla applies configurable rules to propagate non-breaking changes and alerts on breaking ones, minimizing pipeline downtime. Change data is delivered as a Nexset.

One Stream. Any Consumer.

A Nexset from a streaming or CDC source is reusable across every consumer without rebuilding the pipeline. Load it to Snowflake or Databricks for analytics. Sync it back to Salesforce or HubSpot via Reverse ETL. Serve it to an AI agent in real time via MCP. Deliver it to a partner via a secure API.

Transform and Enrich Data In Flight

Apply transforms to streaming and CDC data before it reaches the destination. Filter events, enrich records with reference data, mask PII, combine streams with batch sources, or reshape schemas, all without stopping the pipeline. The Nexla Designer previews results and flags errors as you work.

Enterprise DataOps for Real-Time Pipelines

Nexla provides built-in monitoring, alerting, and schema evolution for all streaming and CDC flows. Data validation runs continuously. Nexla flags records that fail quality checks and routes them to a dead-letter queue rather than letting bad data flow to agents or analytics.

Secure Real-Time Data from Source to Consumer

Nexla enforces security across every real-time pipeline. Data is encrypted in motion and at rest. Credential pushdown means source credentials never leave the pipeline boundary. PII fields are masked or hashed at the transform layer before data reaches any destination.

Ready to Improve Real-Time Visibility and Scale with CDC?

Ask Nexie

Your friendly Nexla companion.
Have a question about Agent Ready Data, MCP Gateway and Server, or SDKs for Coding Agents? Nexie can answer those and anything related to Agentic Data Integration or Data for Agents.