For which editions is Celigo sync available? Standard, Professional, and Enterprise editions; contact your account manager for an add-on subscription
Celigo sync is a data ingestion pipeline designed to simplify moving operational data into analytical destinations at scale. It extends Celigo’s established integration platform with a modern, app-driven data ingestion experience that provides an efficient way to load data from hundreds of applications into your data warehouse.
Data engineering best practices prescribe how to bring data into a cloud data warehouse or lakehouse environment. Building on industry standards and visionary data integration leadership, Celigo sync streamlines and simplifies the process to provide a much smaller set of configuration steps.
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Data loader allows you to choose a single locally stored file to load into any application. Unlike other flows in Celigo, flows built with Data loader cannot be scheduled and are run on demand when the user is logged in.
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Flows designed in Flow builder and syncs built with Celigo sync share a common runtime, connector set, metadata repository, and user registry. As such, both are capable of extracting data from a source application, transforming it as required and loading it to a data warehouse, but Celigo sync is much faster and more easily configurable than Flow builder.
Furthermore, unlike in a traditional application integration, you don’t have to manage each object in an individual flow, figure out the metadata on your own, and create your own table at the destination. Syncs also proved built-in support for schema drift and governance.
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Built-in support for scanning and categorizing objects in NetSuite and Salesforce accounts
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Export data from all HTTP-based applications: branded applications, databases, and universal (HTTP/REST, FTP, GraphQL, and more) connections
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Ingests full historical data (initial backfill) and supports scheduled incremental syncs (polling)
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Snowflake and NetSuite Analytics Warehouse (NSAW)
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Automatically creates and maintains target tables based on selected source objects
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Applies target-compatible data type mappings
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Supports multiple load behaviors: merge (delta updates), append, or replace
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Uses source-provided metadata where available and otherwise applies built-in schema inference
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Detects schema drift, including:
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New/removed objects (table creation/removal)
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Column add/remove
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Data type changes (widening or narrowing)
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Applies drift actions based on policies configurable at the sync level and/or per object
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Provides lightweight “little-t” transformations to ensure source-to-target compatibility
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Out-of-the-box options include masking, primary key handling, and guided normalization vs flattening for hierarchical data
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Dashboard reporting of loaded row counts per object and overall sync status
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Error reporting in-product plus email notifications
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Event logs record schema drift
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Supports full resync/backfill when needed
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Inherits Celigo platform capabilities including RBAC and standard enterprise access controls