"Our Salesforce team can now fully automate Salesforce data integration by building pipelines to prep and load data themselves. They don't need IT anymore, and they love it."
Adam Hooper
Head of Central Platforms, DPD UK
Real-time CDC replication at production scale
Capture and map source changes, then replicate them to production databases every 60 seconds. Keep data products current at scale without custom scripts or replication headaches.
Trusted by 1,100+ data and ops teams saving millions of IT tickets with Integrate.io
May, 2023
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Production data products break when CDC replication falls behind.
Apps, portals, dashboards, and AI workflows all depend on fresh records. When replication lags, jobs fail, or scripts cannot scale, users see stale data.
Product data falls behind
Internal tools and customer-facing apps show stale records when source changes arrive late.
Reports trail the business
Dashboards and reporting layers lose trust when the latest operational data is missing.
Custom scripts need constant care
Hand-built replication jobs break on schema changes, volume spikes, and source system updates.
Capabilities
Production CDC replication without custom scripts
Track inserts, updates, and deletes, map each change to the right destination, and monitor every run from one place.
Capture every source change
CDC connectors track inserts, updates, and deletes from operational systems without polling or hand-built jobs.
Fresh data every 60 seconds
Keep product databases, warehouses, apps, and reporting layers current with CDC changes replicated every 60 seconds.
Scale CDC replication without lag
Move from thousands to billions of rows without source impact, tuning jobs, or delayed downstream data.
Monitor production freshness
Use run history, alerts, retries, and audit trails to know when data moved and where a job needs attention.
Why Integrate.io Read story
Hands-on teams move faster. IT still sees and controls the work.
Analysts, operators, and engineers can build the pipelines they need, while IT keeps access, standards, and visibility in place.
Fixed-fee pricing
Predictable pricing for growing data work, without tying budget to every row, sync, connector, or client.
Flexible pipeline builder
Build visually, prompt with Helm, or add SQL and Python when they help. Teams closest to the data can own the flow.
White-glove service
A dedicated Solution Engineer guides implementation and production work alongside 24/7 support.
Explore the Platform
Use Integrate.io as the end-to-end data pipeline platform for data management, or plug its modular components into the stack your team already prefers.
40,000+ hours saved. Your turn?
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Growth | Analytics Manager
“Awesome ELT Tool. No code tool, easy to set up/use, nice schedules, price balance!”
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Business Intelligence Architect
“Best Customer Service Ever! They have been the best customer service team I have ever worked with from an outside vendor. Always very responsive, and go above and beyond to resolve issues or instruct on the product.”
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Analytics Manager
Connect the systems your data depends on
Managed sources and destinations, a universal API connector for custom systems, and new connectors built on demand within 24 to 48 hours.
Ready to build on fresher data?
Book a 30-minute demo and see how Integrate.io keeps product and reporting data current.
Talk to an Expert
FAQ
Frequently asked questions
Clear answers to the questions teams ask when evaluating Integrate.io.
Still have questions?
Talk to an expert →What is a real-time data product?
Any app, customer portal, internal tool, or reporting layer that depends on fresh data from your source systems to work correctly.
How fresh is the data?
Integrate.io's change data capture (CDC) replicates database changes as often as every 60 seconds.
Which databases does CDC support?
Common relational databases including MySQL, PostgreSQL, SQL Server, and Oracle, replicating into warehouses such as Snowflake, BigQuery, and Amazon Redshift.
Does CDC put load on our production database?
CDC reads changes from the database log rather than querying full tables, which keeps the load on the source low.
How is this different from batch ETL?
Batch ETL reloads data on a schedule. CDC streams only the rows that changed, so downstream systems stay current without full reloads.