👤 This documentation is intended for Site Administrators on the Cache. To compare different infrastructure options, refer to the documentation here. For instructions on how to cache a table, refer to the documentation here.
The Periscope Cache is part of Data Engine. Data Engine is an add-on feature. Site administrators can contact their Customer Success Manager for additional information.
The Periscope Data Engine stores data in Amazon Redshift clusters or Snowflake's Virtual Warehouse. Periscope is able to cache data from the following databases and integrations:
PostgreSQL is an advanced open-source SQL database with a focus on modern technologies, extensibility, and standards compliance. It is an excellent choice as an all-purpose database or a lightweight data warehouse. Heroku and Amazon Web Services offer excellent Postgres-as-a-service deployments.
MySQL is the world's most popular open-source database. It is a common choice for an all-purpose database, and comes with a mature ecosystem of tools and integrations. Amazon Web Services' Relational Database Service is a quick and easy way to get started with a MySQL database.
SQL Server is a high-performance commercial SQL database from Microsoft. Its ColumnStore index type makes it a good choice as a data warehouse as well as a main database, and its Excel integration is seamless and convenient.
Oracle Database is the original SQL database and the most popular commercial database. Oracle is an excellent choice for a large-scale database with enterprise-grade support for UNIX-based platforms.
Note: Oracle is currently supported only on the Redshift Infrastructure.
Salesforce is the number one CRM solution on the market. With this add-on, data from Salesforce can be used to understand customers, identify sales opportunities, and solve problems faster.
Note: Salesforce is currently supported only on the Redshift Infrastructure.
Amazon Redshift is a fast and scalable data warehouse that forms part of the larger cloud-computing platform Amazon Web Services. Redshift utilizes massive parallel query execution and columnar storage for rapid data retrieval.
To import tables into the cache, please follow the instructions on setting caching strategies.