Simple, fast and cost-effective cloud data warehouse service that meets your data analytics needs at the petabyte level
Tencent Cloud Snova Data Warehouse (Snova) provides you with a simple, fast and cost-effective petabyte-level cloud data warehousing solution. With Snova, you can create an enterprise-class cloud data warehouse with hundreds of nodes in just minutes and efficiently perform routine maintenance tasks. A wide variety of open-source Postgres tools are made available to conduct ad hoc queries and analysis, ETL processing and visual exploration of massive amounts of data in Snova. Moreover, with the seamless integration feature of Snova cloud data, petabytes of data stored in data engines such as COS, CDB and ES can be analyzed with ease.
Snova provides convenient elastic scaling, enabling the horizontal or vertical scaling up to hundreds of nodes in the Cloud Console or using Cloud API with ease. The computing unit, CPU, memory and storage capacity proportionally can be scaled up based on business needs to improve performance and meet the demands of business growth.
Tasks like cluster management, monitoring and maintenance can be completed in the console without your having to worry about the heavy OPS of the underlying infrastructure. Snova is fully compatible with the ANSI SQL 2008 standard, enabling the construction of enterprise-class data warehouses using standard SQL. It supports direct queries of COS data without the need for data preloading.
Snova supports the expansion of COS cloud storage, making it possible to achieve unlimited storage capacity. Working together with a variety of tools and solutions, it supports high-speed data import from multiple sources such as traditional relational databases, CKafka and SCS to achieve convergent analysis of multi-source cloud data.
Snova's storage capacity and computing capability can be scaled linearly based on the MPP framework for distributed high-concurrency processing. Further, Snova supports hybrid row-column storage, allowing you to select the best storage solution based on your business needs. The query engine is deeply optimized, offering a query efficiency several times that of traditional data warehouses.
Dual-node sync redundancy enables imperceptible failover and disaster recovery backup. Distributed deployment and triple-layer protection of computing units, servers and cabinets enhance the security of critical data infrastructure. User clusters are deployed separately and support VPC isolation, offering multiple layers of data access security.
In many fields such as finance and retail, it is essential to conduct aggregated analysis of business data on sales, assets and the supply chain in order to understand corporate operational conditions through data and improve decision-making accuracy and efficiency.
Data distributed across CDB, Oracle and PostgreSQL can be imported into Snova through synchronization or using ETL tools and facilitate operational decision-making by leveraging Snova's ability to analyze multi-source heterogeneous data.
In fields such as internet-based finance, gaming and O2O, it is essential to have a cost-effective method for analyzing petabytes of structured or semi-structured data about user behaviors, system logs and orders.
You can store massive amounts of data directly in COS without having to import the data into Snova in advance. Then, simply write SQL statements to quickly analyze and apply the data in COS.
In the context of data-driven operations, fields such as ecommerce, mobile applications, advertising and media require in-depth statistical analysis and mining of data to assist business decision-making. However, the massive amounts of business data collected have posed a major challenge to companies in these fields. Tencent Cloud Elasticsearch Service is capable of structural queries and supports complex filtering and aggregated statistics, helping customers perform statistical analysis of large volumes of data in an efficient and customized manner, identify problems and opportunities, make business decisions and fully unleash the value of data.