Introducing TigerGraph 3.0
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- Introducing TigerGraph 3.0
This blog is the first in a series to unveil the TigerGraph 3.0 GA release. In this blog, we would like to talk about the motivation behind the release, the benefits to the users and of course, the feature set introduced in this release.
With that in mind, our approach was to follow three key design principles for 3.0 release:
Ease of use: Make it easy for non-technical, new-to-Graph users to quickly onboard and gain value from Graph Databases.
Scale and Performance: Ensure that performance and other enterprise requirements scale seamlessly from TBs to PBs to future-proof customer investments.
Better Together: Make TigerGraph entry into existing customer data environments as frictionless as possible. Basically, ensure TigerGraph can interoperate with other data management tools so that customers can continue to get returns on their previous investments
The detailed Gartner report which is available for download on our website goes into the details of how the new grounding breaking features in 3.0 have helped make the selection as a Cool Vendor. Here’s the link: TigerGraph Named a 2020 “Cool Vendor” in Gartner’s Cool Vendors in Data Management Report.
Importance of Graph in Today’s World
As we announce the release of TigerGraph 3.0 GA version, we would like to step back and take a wider look at the current state of the data management market. Graph is consistently listed as a top 10 technology trend in the past few years. There is a clear, big change in recent times in terms of use of Graph to solve business problems. Businesses are no longer satisfied with knowing what happened in the past. Rather the new use cases in advanced analytics are about predicting future outcomes. Any use cases that require in depth analysis of relationships are a natural fit for Graph. Graph analytics allow the exploration of relationships between entities of interest such as organizations, people and transactions. Graph analytics will grow in the next few years due to the need to ask complex questions across complex data, which is not always practical or even possible at scale using SQL queries. Graph data stores can efficiently model, explore and query data with complex interrelationships across data silos, but the need for specialized skills has limited their adoption to date. So, the key question is: Will Graph DB vendors step up to make Graph databases easily accessible for non-technical users? The answer is yes. TigerGraph 3.0 addresses some of the features to help democratize Graph Analytics.Areas of Product Focus
As with any major software release, there is a need to clearly delineate the design thinking behind the TigerGraph feature set. Prior releases have laid the groundwork for the industry leading Graph Database. In terms of performance and enterprise-level features, TigerGraph is the best Graph database in the market. So, the challenge was to build on top of existing functionality and focus on specific areas to make TigerGraph even more compelling for our customers.
With that in mind, our approach was to follow three key design principles for 3.0 release:
Ease of use: Make it easy for non-technical, new-to-Graph users to quickly onboard and gain value from Graph Databases.
Scale and Performance: Ensure that performance and other enterprise requirements scale seamlessly from TBs to PBs to future-proof customer investments.
Better Together: Make TigerGraph entry into existing customer data environments as frictionless as possible. Basically, ensure TigerGraph can interoperate with other data management tools so that customers can continue to get returns on their previous investments
TigerGraph 3.0 Feature Benefits
Application End Users • Easy exploration of Graph data for non-Graph users using No-Code tooling. • Easier integration with downstream applications through an expanded connector library Application Development • Enhances developer productivity by providing quick Visual tools; • Faster and simpler development of sophisticated queries, through Enhanced Pattern Matching • Modular, reusable, and portable code, through Dynamic Querying • Provides a scalable integration path to take solution into production environment Operations & Administration • At least 10x improvement in Cluster Operations speed • Parallel Installer for concurrent upgrades for all cluster sizes • Easier, UI-based management of user and data access privilegesTigerGraph 3.0 Release Highlights
New features and enhancements in 3.0 touch all areas of the product. Broadly, TigerGraph is divided into three layers: Apps, Database Engine and Platform.
Apps:
No Code Migration from Relational Database • Empower data scientists to access the RDBMS data stores by providing a No-code path to convert schema & load data to TigerGraph No Code Graph Analytics with Visual Query Builder • Help non-technical users to produce and run graph queries simply by drawing the patterns they want, similar to visual data modeling GraphStudio Application • Support for Interpreted mode querying for immediate Query Processing • Full MultiGraph access support in GraphStudio • Internationalization and Localization enhancements in GraphStudio • One-click enablement for User-Defined IndexingDatabase Engine:
User-Defined Indexing • Allow users to access non-key data attributes directly based on usage patterns • Identical semantics to SQL to make sure easy adoption for new Graph users GSQL/Engine Features • Dynamic Querying to improve developer productivity via simpler application code that allows sharing and reuse. • Enhanced Pattern Matching, including Conjunctive Pattern Matching enables developers to express complex search patterns, fully incorporated with GSQL’s signature accumulator-based analytics.Platform:
Easier & Faster Deployment Across Distributed Environment • Empower database administrators to scale up TigerGraph deployments with bigger datasets, in minutes System Management Enhancements • Database Export/Import Utility for easy migration of database instances • New and Improved Installer with 10X speed for installation, upgrades and other management operations. • Enhanced UI with User and License Key management And many more …Community Projects to TigerGraph Ecosystem
In addition to the new features introduced in TigerGraph 3.0 release, there are ongoing contributions from the TigerGraph community that helped with system integration with other data management tools and technologies. Here are a few recent ones: • PyTigerGraph Python connector – pyTigerGraph • Automatic JSON to GSQL Schema conversion • Kafka Integration Data Pipeline Pattern • Alexa TigerGraph Integration • GSQL101 – on a Colab Notebook More details can be found at community.tigergraph.comIndustry Recognition for TigerGraph 3.0
In closing, we wanted to share some exciting news for us at TigerGraph. We are honored to be selected ‘Cool Vendor in Data Management’ by Gartner. This recognition by a leading industry research firm speaks volumes on TigerGraph’s impact and potential to provide Graph Analytics solutions. The latest recognition is not one off. It is part of a trend.
The detailed Gartner report which is available for download on our website goes into the details of how the new grounding breaking features in 3.0 have helped make the selection as a Cool Vendor. Here’s the link: TigerGraph Named a 2020 “Cool Vendor” in Gartner’s Cool Vendors in Data Management Report.
