Yugabyte has been recognized by Gartner as a Cool Vendor in Data Management. Read about what makes YugabyteDB and Yugabyte Platform so cool.
Yugabyte Structured Query Language (YSQL) is [a fully-relational SQL API] that is best fit for scale-out RDBMS applications. The YSQL API is built by reusing the PostgreSQL code (version 11.2) directly, and therefore supports most of the features of a traditional RDBMS, such as joins, partial indexes, triggers, and stored procedures.
Yugabyte Cloud Query Language (YCQL) is [a semi-relational SQL API] that is best fit for internet-scale OLTP and HTAP applications needing massive data ingestion and blazing-fast queries. It supports strongly consistent secondary indexes, a native JSON column type, and distributed transactions. It has its roots in the [Cassandra Query Language (CQL)].
Your Data Architecture: Simple Best Practices for Your Data Strategy. Don't miss this helpful article.
A data lake is totally different from a data warehouse in terms of structure and function. Here is a truly quick explanation of "Data Lake vs Data Warehouse".
The basics of enterprise data management, or EDM, are outlined here for those looking to better manage their company's metadata analytics.
In this post, we'll learn Getting Started With Data Lakes.<br><br> This Refcard dives into how a data lake helps tackle these challenges at both ends — from its enhanced architecture that's designed for efficient data ingestion, storage, and management to its advanced analytics functionality and performance flexibility. You'll also explore key benefits and common use cases.
Big Data Management: Data Repository Strategies and Data Warehouses. Managing huge amounts of structured and unstructured data is crucial to the success of every company that needs systematic organization and governance to ensure their data is of high quality and suitable for analytics and business intelligence applications.