Database Replication and Migration Articles

In this article, we’ll introduce the concept and types of real-time data analytics, a detailed breakdown of the advantages and benefits of real-time data analytics, and real-life examples of how it benefits different industries. Finally, we review the challenges and limitations to watch out for during the implementation.

Looking for the best data integration tools? We have done the groundwork and listed the 10 best data integration tools of 2023.

In this post, we will look at implementing CDC with Apache Kafka, including the advantages and disadvantages. We will explore different methods of implementing CDC, including using Arcion to quickly build a scalable replication pipeline.

In this post, we will cover the basics of Change Data Capture in SQL Server, including native tools that can assist with data migration between the platforms. Using SSMA and SybaseToSQL, we will look at the step-by-step process of migrating from Sybase to SQL Server natively. Lastly, we will look at how to implement a CDC-enabled pipeline with Arcion to replicate data from Sybase ASE to Microsoft SQL Server.

In this article, we will look at what Oracle is, what replication is, and the benefits of using a data replication tool. Lastly, we’ll look at 5 Oracle replication tools that could be used to implement data replication.

In this post, we will cover the basics of Change Data Capture, how it can be applied to Sybase ASE through native tools, and how to implement a CDC-enabled pipeline with Arcion. In the example, we go over a step-by-step example of how to replicate data from Sybase ASE to Snowflake.

Oracle GoldenGate is an extension of Oracle's data offering that enables moving data from one database to another. Its modular architecture gives you the flexibility to extract and replicate selected data records, transactional changes, and changes to data definition language (DDL) across a variety of topologies. In this post we will look at the benefits and limitations of the tool as well as how to implement it.

Oracle CDC, or Oracle Change Data Capture, is a technology that efficiently identifies data that has been added, updated, or removed from an Oracle database. Using Kafka with Oracle is a common way to implement CDC within Oracle databases. Explore how to implement a CDC pipeline using Oracle CDC and Kafka.

In this article, we will take a look at the process involved in the migration of data from Oracle to Postgres. We’ll discuss different stages including assessment, schema migration, functional testing, performance testing, and data migration.

In this blog, we’ll walk you through step-by-step how to set up PostgreSQL streaming replication with no-code platform Arcion and use PostgreSQL built-in replication for streaming.

In this guide, we’ll walk you through what Oracle replication is all about and offer you four easy methods to replicate an Oracle database: full dump and load, incremental approach (table differencing), trigger-based approach, and change data capture.

There are multiple CDC methods available for use with the PostgreSQL database, these methods are similar but require a unique way to detect and specify changes made to your database and create a means of sending the changes to a target system.

Data Lakehouse is a new data solution concept that combines elements of a data warehouse with those of a data lake. In this post, we’ll walk you through what is a Data Lakehouse, its benefits, the technology behind it, and how to use CDC to move data into a Data Lakehouse.

MongoDB Change Data Capture (CDC) is a concept or mechanism that is used to identify and record data changes that occur in a datastore to other datastores in real-time. It is used to synchronize data across the datastores ensuring data consistency for applications and systems by moving data from one data repository to another.

The comprehensive guide covers how to set up MySQL CDC, the three methods of setting up MySQL CDC: use MySQL Triggers, binary logs, and Arcion. We also discussed pros & cons for each method. Follow along with the step-by-step guide.

Streaming SQL is a fundamental component of any modern data architecture as many companies now rely on their ever-increasing data production to make data-driven decisions not minding where the data resides.

A data pipeline is a series of data processing steps that involve the movement of data from one place, usually the source to a destination. In this blog, we’ll walk you through what is a data pipeline, the elements of a data pipeline, how to design a data pipeline, and the important factors for sustainable data pipelines.

Data ingestion can be defined as the process of moving data from one or more sources into a target site for immediate use such as queries and analysis or storage. The data sources may include IoT devices, data lakes, databases, on-premise databases, SaaS applications, and so on from which data is ingested into data warehouses, data marts, or document stores.

A data pipeline is a combination of data processing steps used to move data from a source to a destination also known as a sink. In this guide, we’ll show you the difference between data pipelines and ETL, the elements of a data pipeline, different types of data pipelines, data pipeline architecture examples and more.

Apache Kafka is the most popular streaming tool. Using Kafka is a very common way to build a pipeline with SQL Server to stream data in your SQL Server database. In this overview, we will go over a step-by-step approach to show how this can be done. We will also look at how an equivalent pipeline can also be created with Arcion even more simply.

Database replication is the process of copying data from a source database to one or more target databases. Learn everything you need to know in this complete guide.

What is a data pipeline and what are the best data pipeline tools you need? Read this comprehensive guide to see a detailed comparison on the popular choices in the market.

Data in Salesforce can be synchronized with external systems through Change Data Capture (CDC). This can be beneficial for analytics or to store updated data in a data warehouse.

Cloud data migration costs can vary widely from project to project. Read our latest post to learn how to prepare and efficiently manage your migration costs.

In this guide, we'll walk you through an introduction of Snowflake, how to use Snowflake Streams for Change Data Capture, what are the Stream Types available in Snowflake, and how to set up Snowflake CDC with Arcion.

In this comprehensive guide, we will show you how to load data from MySQL to MemSQL (now SingleStore) in real-time with Change Data Capture.

Microsoft SQL Server is one of the most popular RDBMS in the world. Adding Change Data Capture to MS SQL Server is a popular request for many organizations. In this blog, we will introduce what Change Data Capture is as relates to SQL Server and its application as an audit solution. We’ll walk you through how to enable CDC to migrate data in SQL Server both at the database and table level. Finally, some advantages and disadvantages of SQL Server Change Data Capture to enable you to have a well-rounded understanding if faced with choosing SQL Server as a Change Data Capture solution.

‍This article will focus on the data engineering concept of Change Data Capture, often shortened to CDC. In this article you will be introduced to the concept of Change Data Capture, how CDC fits into a data pipeline, CDC’s role within Extract, Load, Transform (ETL) techniques, how CDC works in real-world scenarios, and the benefits to businesses or organizations that adopt CDC. By the end of the article, you should have a firm understanding of Change Data Capture, its components, and the role it can play in managing rapidly changing data.