TigerGraph Inc. is updating its cloud-based graph database, TigerGraph Cloud, with new features designed to help customers more easily collect and process information.

The company detailed the update today. It also disclosed on the occasion that the number of companies using its software has increased significantly over the past year. It says the TigerGraph Cloud installed base has more than doubled over in the last 12 months. 

“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,” said Jay Yu, vice president of product and innovation at TigerGraph. 

Many analytics projects require the ability to understand relationships between the records being processed. A retailer, for example, may seek to determine whether two e-commerce purchase records can be traced back to the same customer. A better understanding of what customers buy enables retailers to deliver more relevant offers. 

The ability to identify relationships between data points is also important for a variety of other analytics use cases. Those use cases span areas such as the cybersecurity, financial services and logistics sectors. 

According to TigerGraph, traditional databases are often not optimized to analyze relationships between records. Many can perform the task, but not with the speed that demanding analytics applications require. 

TigerGraph Cloud is a so-called graph database. That’s a type of database specifically designed to store and analyze relationships efficiently between records. TigerGraph Cloud is one of the most widely used platforms in the category.

Information can only be loaded into a database if it’s stored in a format the database supports. TigerGraph is expanding the list of information formats that TigerGraph Cloud supports with the addition of Apache Parquet. Originally released in 2013, Parquet is widely used among enterprises because it compresses information and thereby reduces the amount of storage capacity needed for analytics projects.

TigerGraph Cloud’s newly added support for the format should translate into improved usability. Because Parquet is widely used and many developers are already familiar with it, the process of loading data into TigerGraph Cloud should become easier. For added measure, the startup has also updated the platform’s data loading interface to make it simpler. 

The Parquet compatibility is rolling out alongside expanded support for another ubiquitous open-source technology: Kubernetes.

Companies can expand Kubernetes’ default feature set by building extensions that automate container management tasks. Such custom extensions are known as operators. As part of today’s update, TigerGraph Cloud is receiving support for Kubernetes operators that simplify container cluster scaling and data backup tasks.

It includes a set of monitoring tools for spotting potential malfunctions. The company is now upgrading those tools to help administrators more easily monitor the health of their companies’ database deployments. Additionally, it’s making it easier to track user queries and attempts to load new records into the database.

On the back end, TigerGraph Cloud now features several cybersecurity and reliability improvements. The company says the improvements were inspired by observations from several large customers’ deployments of the platform. Additionally, it has made a number of more localized updates designed to ease certain data visualization and time-series data analysis tasks.

TigerGraph Cloud is available in a managed version and an edition that companies can deploy within their own infrastructure-as-a-service environments. The database supports all three major public cloud platforms. For companies that operate their own data centers, TigerGraph also offers a version of its software that can run on-premises.

Image: TigerGraph