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Introduction to data replication

NineData data replication supports data replication between homogeneous and heterogeneous data sources. It is suitable for various business scenarios such as data migration, database expansion and contraction, database version upgrade, remote disaster recovery, active-active server, data warehouse and data lake data integration.

Product advantages

NineData data replication products are based on cloud-native architecture. Compared with traditional data replication products, the advantages lay in security, performance, cost and other aspects.

  • Simple and easy to use: SaaS model, out-of-the-box, without complicated deployment and configuration.
  • High performance: Combined with many core technologies such as real-time log capture, intelligent sharding, transactional concurrency, and hotspot merging, it achieves strong replication performance with incremental replication latency as low as seconds.
  • High reliability: Comprehensive monitoring and alarm mechanism, anomaly detection, self-repair mechanism, and intervenable capabilities to improve task availability. Mechanisms such as incremental replication, multi-version metadata, and seamless task restarts ensure the reliability of tasks.
  • Strong Consistency: The industry's innovative breakpoint resuming technology and transaction consistency synchronization capability can effectively ensure the consistency of replicated data, and cooperate with NineData's data comparison function to ensure data quality.
  • Multi-Cloud, Multi-Database: Providing enterprises with data replication capabilities across various databases in a multi-cloud environment. It also supports data replication for locally hosted and cloud provider databases. It supports a variety of common databases, including MySQL, SQL Server, PostgreSQL, Oralce, Redis, MongoDB, ClickHouse, Doris, SelectDB, Elasticsearch, Kafka, Redshift, Greenplum, SingleStore, StarRocks and more.

Use case

  • Database migration: data migration across regions, clouds, or data sources is required, and scenarios such as self-built databases are migrated to the cloud.
  • Real-time data warehouse synchronization: supports real-time integration of data from multiple data sources in various environments into a unified data warehouse for analysis.
  • Cross-cloud and cross-region disaster recovery: supports continuous data synchronization between the primary IDC and the secondary IDC. If a failure occurs in the primary region, user requests can be switched to the disaster recovery region(secondary IDC) to achieve cross-cloud and cross-region disaster recovery.
  • Active-Action instances: supports two-way real-time synchronization between multiple regions to ensure the consistency of global data.
    • When one instance fails, application traffic will be switched to other health instance, which can achieve the second-level recovery of the business and effectively ensure the high availability of business service.
    • Distribute business traffic to various business units according to a certain dimension of the business. For example, the traffic of each unit is divided according to the area to which the user belongs, so that users can access local data to avoid network delay, and improve user experience. At the same time, each business unit is distributed in different regions, which can effectively solve the problem that the infrastructure of a single region limits business expansion.

Perform Data Replication