STREAMING DATA PIPELINE
Deliver Real-Time Insights with Qlik's Streaming Data Pipeline
Build real-time streaming data pipelines that power instant analytics. Stream, transform, and deliver data continuously to enable live dashboards and smarter, faster business decisions.
Power every decision with continuous, real-time data flow
Move beyond batch processing with streaming pipelines that capture, process, and deliver data instantly, enabling organizations to respond to opportunities and threats as they emerge.
Accelerate business insights across teams and systems
Eliminate batch delays by streaming data continuously from sources to analytics platforms, ensuring every decision is based on current reality rather than historical snapshots.
Automate streaming workflows and enable instant analytics
Configure streaming pipelines through intuitive interfaces that connect sources, apply transformations, and deliver to destinations automatically without complex stream processing code.
Support strategic decisions with trusted, always-on data
Maintain data quality and governance while streaming by applying validation rules, enrichment logic, and access controls in real time without sacrificing low latency.
How does Qlik's streaming data pipeline work?
Step 1 - Connect and stream data from any source in real time
Step 2 - Cleanse, enrich, and transform data as it flows
Step 3 - Analyze and visualize streaming data instantly
Step 4 - Deliver continuous updates to analytics and applications
Why choose Qlik for streaming data pipelines?
Streaming infrastructure with built-in governance
Maintain compliance and data trust in streaming scenarios with lineage tracking, quality monitoring, and policy enforcement that operate on data in motion without impacting latency.
Stream data anywhere in your infrastructure
Deploy streaming pipelines across public clouds, private data centers, and edge locations with consistent capabilities and centralized management regardless of deployment location.
Visual development for streaming workflows
Build streaming pipelines through drag-and-drop interfaces that simplify complex stream processing, while providing scripting options for advanced transformations and custom logic.
Enterprise-scale streaming with sub-second latency
Process millions of events per second with distributed stream processing that maintains consistent low latency even during traffic spikes through intelligent load distribution and auto-scaling.
Trusted for mission-critical streaming analytics
Join organizations that monitor operations, detect fraud, and optimize processes in real time using Qlik's streaming pipelines to deliver instant insights from continuous data flows.
Key capabilities of Qlik's streaming data pipeline
Real-time change data capture (CDC) and replication
Capture every database change as it occurs using log-based CDC that monitors transaction logs without impacting source performance, enabling immediate data replication.
In-flight transformations and data enrichment
Apply business logic, join streams, aggregate events, and enrich data while it flows through pipelines using in-memory processing that maintains sub-second latency.
Integration with cloud warehouses and data lakes
Stream data directly into Snowflake, Databricks, AWS, Azure, and Google Cloud with native connectors optimized for high-throughput ingestion of streaming data.
Event-driven architecture for instant analytics
Build responsive applications that react to data events in real time, triggering workflows, alerts, and automated actions based on streaming patterns and conditions.
Monitoring, alerts, and pipeline observability
Track streaming pipeline health with comprehensive metrics for throughput, latency, errors, and data quality, enabling proactive optimization and rapid issue resolution.
Secure, governed streaming and access control
Protect streaming data with encryption in transit, role-based access controls, and audit logging while maintaining the low latency required for real-time operations.
Trusted by leading enterprises worldwide
What our customers say
We needed to consolidate data in one place, from heterogeneous sources, updated in almost real-time. That’s what Qlik enables for us.
Connect to 500+ data sources with Qlik’s analytics integrations
SAP
Adobe
IBM
AWS
MySQL
Jira
Azure
MS SQL
Apache
Mongo DB
SAP
Adobe
IBM
AWS
MySQL
Jira
Azure
MS SQL
Apache
Mongo DB
SAP
Adobe
IBM
AWS
MySQL
Jira
Azure
MS SQL
Apache
Mongo DB
SAP
Adobe
IBM
AWS
MySQL
Jira
Azure
MS SQL
Apache
Mongo DB
SAP
Adobe
IBM
AWS
MySQL
Jira
Azure
MS SQL
Apache
Mongo DB
Oracle
Salesforce
Workday
Apache Iceberg
CircleCI
Zendesk
Snowflake
Databricks
OpenAI
Intuit
Oracle
Salesforce
Workday
Apache Iceberg
CircleCI
Zendesk
Snowflake
Databricks
OpenAI
Intuit
Oracle
Salesforce
Workday
Apache Iceberg
CircleCI
Zendesk
Snowflake
Databricks
OpenAI
Intuit
Oracle
Salesforce
Workday
Apache Iceberg
CircleCI
Zendesk
Snowflake
Databricks
OpenAI
Intuit
Oracle
Salesforce
Workday
Apache Iceberg
CircleCI
Zendesk
Snowflake
Databricks
OpenAI
Intuit
Resources
Streaming data pipeline FAQs
Streaming processes data continuously as it arrives rather than collecting and processing in periodic batches, enabling immediate insights and actions based on current data instead of delayed batch results.
Yes, elastic scaling automatically adds processing capacity during traffic spikes while backpressure handling prevents overwhelming downstream systems, maintaining reliable operation during demand variation.
Checkpoint recovery and automatic reconnection ensure pipelines resume from the last processed position without data loss, maintaining exactly-once processing semantics during disruptions.
In-flight validation applies quality rules to streaming data in real time, with options to quarantine bad records, generate alerts, or apply automated corrections without stopping the stream.