Highlights:
- TigerGraph Inc. is upgrading TigerGraph Cloud, its cloud-based graph database, with new capabilities meant to make it easier for users to collect and analyze data.
TigerGraph Inc. is upgrading TigerGraph Cloud, its cloud-based graph database, with new capabilities to make it easier for users to collect and analyze data.
The business released further information on the change recently. It also revealed that the number of organizations utilizing its software has climbed dramatically over the last year. According to the company, the installed base of TigerGraph Cloud has more than quadrupled in the previous year.
Jay Yu, vice president of product and innovation at TigerGraph, said, “Graph is a crucial tool for solving business challenges, and TigerGraph is committed to helping customers unlock the full potential of their data by using ML and AI to close the gap between data and decisions.”
Many analytics projects need awareness of the relationships between the processed records. For instance, a store may assess if two e-commerce purchase records may be linked to the same consumer—a more profound comprehension of what clients purchase helps merchants provide more relevant offers.
Identifying correlations between data elements is also crucial for various other analytics applications. These use cases cover several industries, including cybersecurity, financial services, and logistics.
TigerGraph states that standard databases are frequently not designed to analyze record connections. Several can do the work, but not with speed required for demanding analytics applications.
TigerGraph Cloud is a graph database. This database is developed mainly to store and analyze relationships between records effectively. TigerGraph Cloud is one of the category’s most popular platforms.
Only data stored in a format supported by the database can be imported into it. Apache Parquet has been added to the list of supported data formats for the TigerGraph Cloud. Parquet, which was initially introduced in 2013, is frequently utilized by businesses since it compresses data and minimizes the storage space required for analytics projects.
TigerGraph Cloud’s newly added support for the format should result in a more intuitive usability. As Parquet is extensively utilized and many developers are already familiar, importing data into TigerGraph Cloud should become simpler. In addition, the firm has revamped the platform’s data-loading interface to make it easier to use.
The Parquet compatibility is launching with the expanded support for Kubernetes, another ubiquitous open-source technology.
The default feature set of Kubernetes may be expanded by constructing extensions that automate container management operations. Such tailored extensions are referred to as operators. As part of the recent release, TigerGraph Cloud now supports Kubernetes operators that facilitate growing container clusters and data backup chores.
It consists of a collection of monitoring instruments for detecting possible problems. The firm is currently updating these tools to make it easier for administrators to monitor the health of their organizations’ database deployments. Moreover, it facilitates tracking user searches and attempts to load new entries into the database.
TigerGraph Cloud’s backend has undergone significant security and reliability enhancements. According to the business, the upgrades were motivated by findings from the platform installations of numerous significant customers. In addition, several customized improvements have been implemented to facilitate specific data visualization and time-series data analysis activities.
TigerGraph Cloud is offered in a managed edition and a version that businesses may implement inside their infrastructure-as-a-service setups. The database is compatible with all three largest public cloud platforms. TigerGraph also provides a version of its software that may run on-premises for businesses that manage their data centers.
