List of IBM Change Data Capture Customers
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Since 2010, our global team of researchers has been studying IBM Change Data Capture customers around the world, aggregating massive amounts of data points that form the basis of our forecast assumptions and perhaps the rise and fall of certain vendors and their products on a quarterly basis.
Each quarter our research team identifies companies that have purchased IBM Change Data Capture for Extract, Transform, and Load (ETL) from public (Press Releases, Customer References, Testimonials, Case Studies and Success Stories) and proprietary sources, including the customer size, industry, location, implementation status, partner involvement, LOB Key Stakeholders and related IT decision-makers contact details.
Companies using IBM Change Data Capture for Extract, Transform, and Load (ETL) include: Mizuho Bank Japan, a Japan based Banking and Financial Services organisation with 23827 employees and revenues of $62.28 billion, Universal Sompo General Insurance, a India based Insurance organisation with 3000 employees and revenues of $520.0 million, BITMARCK GmbH, a Germany based Professional Services organisation with 1438 employees and revenues of $348.0 million and many others.
Contact us if you need a completed and verified list of companies using IBM Change Data Capture, including the breakdown by industry (21 Verticals), Geography (Region, Country, State, City), Company Size (Revenue, Employees, Asset) and related IT Decision Makers, Key Stakeholders, business and technology executives responsible for the software purchases.
The IBM Change Data Capture customer wins are being incorporated in our Enterprise Applications Buyer Insight and Technographics Customer Database which has over 100 data fields that detail company usage of software systems and their digital transformation initiatives. Apps Run The World wants to become your No. 1 technographic data source!
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| Logo | Customer | Industry | Empl. | Revenue | Country | Vendor | Application | Category | When | SI | Insight | Insight Source |
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BITMARCK GmbH | Professional Services | 1438 | $348M | Germany | IBM | IBM Change Data Capture | Extract, Transform, and Load (ETL) | 2014 | n/a | In 2014, BITMARCK GmbH implemented IBM Change Data Capture as an Extract, Transform, and Load (ETL) application to stream transactional changes into its BI and data warehouse landscape. The deployment targeted BITMARCK's healthcare customer data flows in Germany and supported enterprise reporting and analytics workloads. IBM Change Data Capture was configured to capture change data from DB2 and other operational sources, apply light transformation and staging logic, and deliver incremental streams into the warehouse for near continuous ingestion. The implementation leveraged change data capture pipelines, log based change capture and delivery workflows common to Extract, Transform, and Load (ETL) solutions. BITMARCK historically used IBM Q Replication / InfoSphere Data Replication to replicate DB2 and other sources into its BI and warehouse landscape before moving to alternative replication tooling. Integrations centered on DB2 source systems and the central BI and data warehouse targets, with operational ownership assigned to BITMARCK's data engineering and BI teams. Governance emphasized ingestion orchestration, schema change control and replication job scheduling to enable self service reporting, improving real time data availability for healthcare clients in Germany. | |
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Mizuho Bank Japan | Banking and Financial Services | 23827 | $62.3B | Japan | IBM | IBM Change Data Capture | Extract, Transform, and Load (ETL) | 2012 | n/a | In 2012, Mizuho Bank Japan deployed IBM Change Data Capture as part of an Extract, Transform, and Load (ETL) approach to enable high-availability replication for core transactional systems. The deployment emphasized active-active DB2 replication to support the bank's online and mobile banking operations in Japan and to improve continuity and analytics. The implementation leveraged IBM InfoSphere Data Replication and Q Replication modules as reported in partner solution listings, with IBM Change Data Capture configured to provide continuous change capture and bidirectional replication between DB2 instances. Configuration work focused on change data capture streams, replication topology, and ensuring transactional consistency across active nodes. Integrations explicitly included DB2 database instances and the bank's online and mobile banking application tiers, with replicated data feeding continuity processes and downstream analytics consumers. Operational coverage targeted production banking systems in Japan, aligning replication windows and monitoring to support real-time data availability for operational and analytical functions. Governance centered on replication topology control, failover orchestration, and operational monitoring for replication lag and data consistency, with configuration management for Q Replication and InfoSphere Data Replication components. IBM Change Data Capture functioned as the primary change capture layer within the ETL architecture, instrumenting continuous data movement to support continuity and analytics use cases. | |
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Universal Sompo General Insurance | Insurance | 3000 | $520M | India | IBM | IBM Change Data Capture | Extract, Transform, and Load (ETL) | 2015 | n/a | In 2015, Universal Sompo General Insurance implemented IBM Change Data Capture as part of an Extract, Transform, and Load (ETL) initiative to centralize data and address siloed applications and the lack of a central repository. Business users and actuarial teams were previously performing significant manual consolidation to produce day to day reports and insurance specific KPIs. The deployment architecture used IBM Change Data Capture to replicate transactions in real time from core insurance applications running on AS/400 into an Operational Data Store. IBM Datastage served as the data integration and transformation engine to process and normalize input data and subsequently populate a star schema in IBM Db2 Warehouse, with IBM Change Data Capture providing continuous incremental feeds. Purpose built data marts were provisioned on top of the Db2 Warehouse and IBM Cognos Analytics was used to develop key reports and KPI dashboards including Revenue Per Policyholder, Average Cost Per Claim, Loss Ratio and Underwriting Speed. Actuarial users accessed consolidated datasets in the ODS and warehouse to build and test predictive models such as persistency reporting, customer churn and campaign analytics, while business users gained self service reporting capability. Governance and rollout focused on central availability of validated source data and reworking reporting workflows to reduce IT bottlenecks, shifting operational reporting, actuarial modeling and analytics processes across underwriting, claims and finance. Stated benefits included real time visibility of source system data in the ODS, improved tracking of insurance KPIs, implementation of key predictive models and reduced IT intervention for routine report generation. |
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