CData Sync

A new year brings new capabilities! We’re excited to kick off 2026 with one of our largest CData Sync releases yet, this Q1 roll out is packed with enhancements designed to give you more flexibility, control, and power across your data pipelines. Here’s what’s new in Sync Q1 2026: ❄️ Apache Iceberg Destination Support CData Sync now supports the Iceberg file format and catalog, enabling modern lakehouse architectures with open, reliable table formats. Iceberg destinations are now available for:  Amazon S3  Azure Blob Storage  Azure Data Lake Storage  Google Cloud Storage  🚦 Visual Pipelines in the UI We’re excited to preview Pipelines, an upcoming point-and-click UI experience for managing job and event dependencies in Sync. Pipelines will make it easier than ever to orchestrate and visualize Sync workflows.🔄 CDC Catalog Enhancements: SAP HAN

Hi,I’m trying to use Sync to replicate data from Salesforce into a Postgres database.  I have a full load working, and every night it truncates then reloads the tables.I’m having a lot of problems setting up another job that then runs an incremental update periodically.  It seems straightforward to set up.  My jobs incremental settings are:Start Date:  2026-01-06 Replication Interval : 1 dayWhen I run the job, I consistently get the same error, regardless of which Salesforce object I try to incrementally update.  In this case my source is Building__c, and the destination is the Postgres table salesforce.building. The error I get is:  [0] Updating Row is failed. ERROR: Server error [SQL state: 42P01]: relation "salesforce_building__r_1329269084" does not exist (Character 13) , AffectedCount: 0I can’t find any mention of this type problem in the documentation, and have followed all the steps in the docs to set this up.

When configuring a replication Job after creating a Connection to your SQL Server database, you may initially find that you are unable to utilize this Connection as a Destination.The Connection appears as intended when selecting a Source for the Job:However, the same Connection does not appear when selecting a Destination:What can be done to resolve this?

The CData Sync clustering feature allows multiple Sync installations to operate together as a single, scalable, and highly available environment. By distributing workloads across multiple nodes, clustering ensures continuous operation, automatic failover, and consistent performance even as data movement needs grow.In this article, you’ll learn how to: Set up Sync nodes to share a unified application directory Configure a shared application database for consistent metadata and job management Enable and activate Cluster Mode across all Sync installations Ensure reliable, distributed job execution with automatic node balancing To learn more, read: Configuring Clustering for CData Sync

Working with PostgreSQL data that includes “Infinity” values? Learn how to manage and sync these special values effortlessly using CData Sync. Our newest guide walks you through the necessary steps and best practices to keep your data clean and reliable.Full guide: https://www.cdata.com/kb/articles/sync-postgresql-infinity-values.rst

Hey CData Community!Microsoft’s SQL Server 2025 brings AI into the heart of the database with new native vector support, enabling you to store, search, and analyze embeddings directly inside SQL Server. When paired with CData Sync, you can easily connect and replicate data from 250+ sources to power AI workflows like semantic search, RAG pipelines, and anomaly detection — all within SQL Server.Check out the full guide here: https://www.cdata.com/kb/articles/sync-sqlserver25-ai-workflows.rst

Fall is here and so is CData Sync’s Q3 2025 release! Our latest updates are designed to help you unlock more value from your data, faster and more efficiently. ⚡ Enhanced CDC Catalog Expansion: You asked, we delivered Sync now supports DB2 protocol AS400/iSeries and MySQL for even broader data replication capabilities! 🔄 Reverse ETL Catalog Expansion: New destinations now supported, including Salesforce Pardot, Salesforce Marketing Cloud, Sage Intacct, and Veeva Vault to enhance your reverse ETL capabilities ✨ Open Delta Table Support: Now available for all your favorite data lake destinations such as: Amazon S3, Azure Blob Storage, Google Cloud Storage, and Azure Data Lake Storage powering your delta integrations across Databricks, Fabric, and more! ⚡ Faster File Replication: CSV, Avro, Parquet, and One Lake Mirroring are now 90% faster for smoother large-workload handling. 🛠 Generic JDBC Connector: Unlock source-only connectivity and schema disco

Most ETL/ELT tools provide connectivity to Workday; however, the connection is limited because it is only through Reports as a Service (RaaS). With the CData Sync Workday connector, users get more connection options, including support for:Prism Data Catalog Workday Query Language (WQL) RaaS REST API SOAP APIOur latest article reviews how the Workday connector for CData Sync delivers full connectivity when compared to other ETL/ELT tools' connectors.Read the full article: https://www.cdata.com/kb/articles/workday-sync.rst

We’re excited to share the latest updates in CData Sync, now live with powerful new features designed to elevate your data integration experience: 🔁 Microsoft Mirroring as a Destination In partnership with Microsoft, Sync now supports OneLake Mirroring, enabling direct ingestion into the Microsoft Fabric ecosystem. With native Parquet support and catalog integration, it's a seamless way to accelerate your lakehouse strategy. 📈 CDC for SAP ERP Deliver near real-time replication from SAP ERP systems using RFC, expanding our enterprise-grade CDC coverage. 🔐 Stronger Identity & Access Management Enjoy a smoother, more secure experience with revamped SAML integration and 2FA 🌟 Coming in July!  New Reverse ETL Destinations: Pardot, Sage Intacct, and Salesforce Marketing Cloud  Open Table Format Support: support for DeltaLake on AWS, Azure, and GCP.  📚 View full release details in th

Hey CData Community!Looking to bring your Salesforce data into SAP Datasphere without the headaches? Our latest post, Replicate Salesforce Data to SAP Datasphere with CData Sync, walks you through the full setup — from database user creation to job execution — so you can get your external data flowing into Spaces fast.No native connector? No problem. With CData Sync, you can plug in Salesforce (or any of 270+ sources) and start building with real-time, reliable data. Check out the full guide here: https://www.cdata.com/kb/articles/sync-sap-datasphere.rst

Hey CData Community!Manually enabling Change Tracking for every Dynamics 365 entity? That is a lot of effort.Good news. CData Sync can do it for you using a stored procedure.It automatically enables Change Tracking for the right entities so you can set up incremental replication without the manual work.Want to see how it’s done? Check it out here: https://www.cdata.com/kb/articles/dynamics365-change-tracking.rst

Hey CData Community!Just dropped: a quick deep-dive on the new Enhanced CDC feature in CData Sync• 9× faster replication (10 k changes: 6 s vs 54 s)• Always-on log reading + staging area = reduced wait at run time• Step-by-step setup, benchmarks, and diagrams inside Refer to the following link to read the post: https://www.cdata.com/kb/articles/sync-enhanced-cdc-performance.rst

Hi,I have 3 years worth of data. All the data stay the same but the latest 3 months are dynamic. I need to replace the old data with the latest data. But if I do “Drop Table”, it drops all the data and bring all 3 years worth of data and sometimes the system dont seem to be able to handle it.  I would like to keep everything and just have the last 3 months tables dropped and replaced. I dont want the system to have to bring ALL data from the past 3 years. I just need the last 3 months dropped and replaced.  What setup should I do?

Hey CData Community!Moving large volumes of data into Snowflake just got a major performance upgrade. With the release of CData Sync version 24.3, high-volume data replication is now significantly faster and more efficient, cutting job completion times nearly in half for optimized processes.In our recent article, we looked at the enhancements made to CData Sync’s processing engine and explored how these improvements play out across datasets ranging from 1 million to 10 million records.Learn More: https://www.cdata.com/kb/articles/sync-snowflake-performance.rst

Hi,I have Sync version 24.3.9120.0 and I’m using Apache Kafka as source. It’s working fine, except little irritation. When I run task it will replicate only first 150 000 rows and stops after that. Next time I run the task, it replicates 179 000 rows and so on. Row count will increase. Seem to be randomI can run job multiple times and it will continue where it was stopped earlier. Is there way to change this behavior, so that all rows will be replicated at once?

Since the update to Sync version 25.1.9207 we are getting some strange errors from different tasks.All these tasks worked without problems before the update.So far i have not found any difference (except for the tables) between tasks that work and that won’t work. It even fails on small datasets (19 in this example, a 16.000.000+ tasks works without problem)And the log also is not showing a lot of info:2025-03-25T12:34:16.494+0100    2    [ |Q-Id| T-Id]    [ |Q-Id]    [SQL |Bulk  ] 15 rows are being committed.2025-03-25T12:34:16.494+0100    5    [    2|    0| 1164]    [CORE] [RealDB:SQLServer]Starting WriteToServer2025-03-25T12:34:16.494+0100    5    [    2|    0| 1164]    [CORE] [RealDB:SQLServer]Invoke WriteToServer2025-03-25T12:34:16.508+0100    1    [    2|    0| 1164]    [CORE] [RealDB:S

Spring is here, bringing fresh updates to CData Sync! Our latest enhancements are designed to streamline your data integration and management, helping you bloom with efficiency this season: 📂 Workspaces for Better Organization: Easily group Jobs, Connections, and Transformations under Workspaces for improved management and streamlined workflows. Users now have greater control over the processes and data, ensuring a more structured and efficient Sync experience. ⚡ Enhanced CDC Catalog Expansion: You asked, we delivered—now supporting DB2 LUW and Informix for even broader data replication capabilities! 🔄 Reverse ETL Catalog Expansion: We are adding Oracle as source and destinations such as Kintone, HubSpot and Zoho CRM to enhance your reverse ETL capabilities! 🛠️ Destination Performance Improvements: Experience faster data processing with increased performance for our Databricks & Redsh

CData Sync supports the execution of ELT processes flexibly using dbt Core or dbt Cloud. This integration gives users complete control over defining and executing complex data transformation workflows in dbt, while CData Sync provides a pipeline for users to run those transformations in your chosen destination. Read more about using dbt Core or dbt Cloud with CData Sync here:dbt Core: https://www.cdata.com/kb/articles/sync-dbt-core.rstdbt Cloud: https://www.cdata.com/kb/articles/sync-dbt-cloud.rst

Hi there.Is there a way of replicating data in batches.We are looking at a lambda approach with small incremental replication, followed up with a weekly full reload to catch late-arriving data and physical/hard deletes.The challenge is that the full reload data volumes are too large for the server hosting our CData Sync. Even with the JAVA heap adjustments.I was wondering if we could do the reload/replication in a looping process.  The source is Snowflake the target is Azure ADLS2 parquet files.

CData Sync can be deployed in a Kubernetes environment. This allows users to take advantage of Kubernetes’ orchestration functionality, including high availability (no downtime), scalability of loads, and backup-and-restore capabilities.Read more about this and follow our guide for this deployment here:https://www.cdata.com/kb/articles/sync-kubernetes.rst

Hey CData Community!Slowly Changing Dimensions (SCDs) are essential in data warehousing to manage and track changes in dimension data over time.With CData Sync, users can easily implement these SCD models. In our recent article on how to implement SCD using CData Sync, we introduce the most common types—Types 1 to 3—and explain how CData Sync enables you to configure and automate the management of these SCD types without writing any code, making it accessible to users of all technical levels.Read here to know more: https://www.cdata.com/kb/articles/slowly-changing-dimensions.rstIf you have additional questions, please let us know!

CData Sync can be deployed to Microsoft Internet Information Services (IIS), which enables businesses to host Sync as an externally facing website. This allows organizations to utilize the advanced features of IIS, all while keeping the simplicity and functionality of CData Sync's embedded web server.Read more about the two methods you can use to deploy CData Sync in IIS here: Sync IIS Java deployment

Table of Contents Introduction Overview of CData Sync Overview of Terraform Benefits of CData Sync automation with Terraform Prerequisites Terraform configurations VPC module EC2 module Parent module DEMO: CData Sync automatic deployment on AWS Conclusions Key Considerations IntroductionIn today's rapidl

CData Workday Drivers and Connectors now allow users to create tables that execute specific Workday Query Language (WQL) statements for Workday reports. The new stored procedure, CreateWQLSchema, processes the output from Workday's "Convert Report to WQL" task and retrieves the same report data using the WQL statement. Read more about this Workday Driver enhancement here:Workday: How to Access Live Data from the WQL for a Workday ReportIf you have additional questions, please let us know!

Hi all,Our team is using CData Sync to extract and load data from SQL Server to Snowflake. The source MSSQL table is CDC-enabled, and we have created a CData Job with Change Data Capture enabled. We started testing the task with smaller tables (containing 100K - 300K records), and the task was successful without any issues. However, when trying with larger tables (containing 10M - 35M records), we faced failures every time.I have attached the error output for your reference. Has anyone come across this scenario? Any replies or help would be much appreciated. Thanks in advance.Error output: "2024-11-14T02:25:19.555+0000 2 [32|Q-Id] Failed to cache row [501097] The query was canceled."We tried running the same task with a few manipulations, like reducing the source table records to 1M over 10M but had no luck. We are not facing any other issues besides "Failed to cache row." What does caching mean in a CData