Arcion Unveils Agentless Change Data Capture for Azure, SQL Server, Oracle, SAP HANA, and MySQL


Arcion, creator of the only cloud-native, CDC-based data replication platform, today announced agentless change data capture (CDC) for all of its supported databases and applications. Enterprises can now replicate data in real time, at scale, with guaranteed delivery — but without the inherent performance issues, security concerns, and administrative burdens associated with the installation of proprietary software on database servers.

Arcion enables faster, more agile analytics and AI by replicating mission-critical transactional enterprise databases to cloud-based data platforms in real time, at scale, and with guaranteed transactional integrity. It is the only fully managed, distributed data replication-as-a-service on the market today that makes it possible to deploy zero-code, zero-maintenance pipelines in just minutes.

Unlike its nearest competitors, Arcion provides agentless CDC for all supported platforms, including Microsoft Azure and SQL Server, Oracle, DB2, SAP HANA, Salesforce, PostgreSQL, MongoDB, Snowflake, MySQL, and numerous others. Agentless CDC eliminates the need to install and manage proprietary software on the database server. This offers three primary benefits: better performance, simplified compliance, and substantially lower administrative costs.

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“Arcion’s agentless approach offers simplicity and peace of mind,” said Rajkumar Sen, chief technology officer at Arcion. “Providing maximum flexibility and agility, data engineering and IT teams can deploy streaming pipelines in minutes, without the typical planning cycles and dependencies often associated with agent-based solutions. With Arcion, data engineers can now deploy streaming replication pipelines without extensive database administrative changes and IT reviews and, at the same time, significantly reduce the risk of a security breach. They get scalable real-time data replication without the administrative nightmares and risks associated with running agent-based software on production cloud environments. For performance, flexibility, and total cost of ownership, agentless CDC wins every time.”

The agentless approach provides real-time replication without adversely affecting the performance of the database server. Arcion reads directly from database logs, never reading from the database itself and never deploying any code on a production system. As such, it does not consume substantial computational resources on the database server, even at volume.

Arcion’s agentless CDC model also operates outside the scope of restrictions commonly imposed by application vendors and hosting providers. Application vendors like SAP and Oracle, for example, limit the installation of third-party code on their database servers — or even prohibit it altogether. In some cases, vendors may require extensive certification (and frequent recertification) before allowing software to be installed alongside the database. Arcion requires no such installation, making it fully available for any supported platform, regardless of vendor policies.

Finally, Arcion’s agentless model dramatically reduces IT administration by eliminating the need to install and update software on database servers. For companies that run hundreds or even thousands of database instances, the cost of these administrative tasks can be extraordinarily high. As well, deploying an agent on a database server increases the need to add compute capacity to those systems, which causes rapid growth in both hardware costs and licensing fees as data volumes increase. Arcion’s agentless model does away with administrative duties altogether and contains the cost growth of production systems, dramatically reducing the total cost of ownership.

On Oct. 13, 2022, Databricks will join Arcion to host a free webinar, “Modernize Your IBM Mainframe and Netezza With Databricks Lakehouse,” discussing the role of CDC in migrations and ongoing replications with IBM Mainframe data and how to implement production-level CDC pipelines from IBM Mainframe, Netezza, and Informix to the Databricks Lakehouse.

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