Real-Time Data Integration

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:

  • Event streams: Kafka, Amazon Kinesis, Google Cloud Pub/Sub, JMS, Azure Event Hubs
  • Change Data Capture: databases including Postgres, MySQL, Oracle, SQL Server, and MongoDB
  • Webhooks: incoming and outgoing, any REST endpoint
  • Legacy sources via CDC bridge: mainframe, ERP systems
Nexla: Connect Any Streaming Data

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. That consistency is what makes real-time data reusable across agents, analytics, and operations without rebuilding pipelines for each use case.

Nexla: Create Streaming Data Products

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. No full table scans. No bulk reloads. 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, so the same CDC feed can serve a Snowflake warehouse, a Kafka topic, an operational application, or an AI agent via MCP all from the same connection.

Nexla Build for Change - Modern DataOps

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. The integration style – batch, real-time, MCP, API, is chosen at the flow level, not baked into the connection. Build once. Serve any consumer.

Nexla: Reuse Streaming Data Across Projects

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. Use the Nexla visual designer, AI prompts, or SQL, Python, or JavaScript for custom logic. Transforms run in-flight on each event or change record. The Nexla Designer previews results and flags errors as you work, so data quality issues surface before they reach downstream consumers.

Prepare and Transform Data Easily with Nexla

Enterprise DataOps for Real-Time Pipelines

Nexla provides built-in monitoring, alerting, and schema evolution for all streaming and CDC flows. Schema changes at the source are detected as they occur. Nexla applies rules to propagate non-breaking changes automatically and alerts immediately on breaking changes, reducing manual intervention and avoiding full pipeline restarts. 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. All flow activity is logged with lineage so every data access is traceable to its source.

Nexla: Powerful Streaming DataOps and Monitoring

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, internal or external. Agent identity flows from the MCP client through the data layer to the source — every agent data access is authenticated, authorized, and auditable. Nexla does not store data: all data products are virtual. Deploy in Nexla cloud, your private cloud, or on-premises. SOC 2 Type II, HIPAA, GDPR, and CCPA compliant.

https://nexla.com/data-security/
Keep Data Secure with Nexla's Enterprise Security: SOC 2 Type II, ISO, HIPAA, and GDPR Compliant

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