Change Password

Please enter the password.
Please enter the password. Between 8-64 characters. Not identical to your email address. Contain at least 3 of: uppercase, lowercase, numbers, and special characters.
Please enter the password.

Change Nickname

Current Nickname:

Apply New License

License Detail

Please complete this required field.

  • Ultipa Graph V4


Please complete this required field.

Please complete this required field.

The MAC address of the server you want to deploy.

Please complete this required field.

Please complete this required field.

Applied Validity Period(days)
Effective Date
Excpired Date
Mac Address
Apply Comment
Review Comment
  • Full Name:
  • Phone:
  • Company:
  • Company Email:
  • Country:
  • Language:
Change Password

You have no license application record.

Certificate Issued at Valid until Serial No. File
Serial No. Valid until File

Not having one? Apply now! >>>

Product Created On ID Amount (USD) Invoice
Product Created On ID Amount (USD) Invoice

No Invoice

Ultipa Raises $21M In Series A - Ultipa Graph
Ultipa Raises $21M In Series A - Ultipa Graph

The high-performance graph database solution provider, Ultipa, secures $21M in Series-A financing led by a well-known sovereign fund, and its angel investor, CMB International, co-invests in this round of fundraising.

Founded in 2019, Ultipa gathers a group of talents who previously worked in high-tech MNCs like Microsoft, HP, EMC, Alibaba, etc. Ricky Sun, the founder and CEO, is a serial entrepreneur with 20+ years of experience in Silicon Valley and Beijing. He is also a world-class expert in fields of high-performance systems, big-data and cloud computing, and previously CEO of, CTO of EMC CCOE, Managing Director of EMC Labs China, and Chief Architect of Splashtop OS (predecessor of Chrome OS). Monica Liu, co-founder and COO, held various managerial posts in world-famous companies like Compaq/HP, Guidant/Abbott. Other key members graduated from Tsinghua, Harvard and other prestigious universities from around the world, with many decades of combined solid and cutting-edge technological training and world-class vision.

Graph databases are destined to replace traditional RDBMS

Ricky realized when he was earlier engaged in high-performance system building and big-data-related works in Silicon Valley, that the relational database, which had existed for 40 years, increasingly showed its incompetency in meeting the needs of high-dimensional, sea-volume, dynamic data processing. Hadoop, the cure to dealing with big-data in the old days, is notoriously famous for its poor performance; even when Spark came, the data throughput and processing capacity were still not satisfactory, especially in financial industry scenarios. Graph databases were very rare in the world, most were built upon traditional RDBMS, Hadoop or other NoSQL DBs, not to mention high-performance native graph DB solutions.

As a result of the increasing demand for the digital transformation of global enterprises, the capabilities of multivariate analysis against multimodal data within the context of big-n-fast-n-deep data processing are highly sought after. These real-world business challenges can hardly be solved with traditional databases or data warehouses -- for instance: real-time decision-making, intelligent marketing, anti-money-laundering, anti-fraud and other emerging business needs. Fortunately, graph database is one tangible solution -- it's high-dimensional and born to deal with dynamic, multi-modal data sets, especially its deep-data processing capability. Ricky further explained that "the next decade will witness the rapid development of graph database, that the traditional, low dimensional databases will gradually be replaced by high dimension graph DBs."

Graph DB powered solutions are the ultimate answers to financial scenarios

Supported by its rich collection of products - Ultipa Server, Ultipa KG, Ultipa Toolkits &SDK - Ultipa has yielded many successful BFSI scenarios such as liquidity risk management in ALM (Assets and Liabilities Management), risk management in AM (Asset Management), Enterprise GRC, Supply Chain Finance and so on. The Ultipa Engine, acclaimed as 'nuclear-powered' by the clients, can calculate 300,000,000 triangles in one second, which has really pushed the limit of the existing X86 computer system; in knowledge graph scenarios, real-time penetration of correlated data for 30-plus hops (layers) makes the Engine a perfect weapon for sophisticated online BI & decision making -- which was not possible with RDBMS/NoSQL or Hadoop/Spark-based solutions.

Figure: Graph database thrusts big-data processing

Customer demand variety defines product deployment flexibility

As of mid-2021, in less than a full year of commercialization, Ultipa has acquired more than 20 customers, including tier-1 retail and commercial banks, securities companies, stock exchanges, and industry-leading MNCs. Ricky explained that ground-breaking technology and top-notch product have to find their ways of making breakthroughs starting with business leaders -- even though doing so may be deemed more challenging in conventional standpoints. This is like traversing the great pyramid from the top all the way to the bottom, conquering the top first makes the whole game a downhill battle.

Since 2019, Ping An Bank, China Merchants Bank (short for CMB hereafter), and several other major banks, securities companies have gone through rounds of in-depth testings with Ultipa, and have signed commercial contracts with Ultipa one after another. Taking CMB as an example, as one of the world's largest retail and commercial banks (Ranked-17th per The Banker,s Top-1000 global banks), it sees bank-wide urgent needs of processing multimodal and inter-correlated data with speed, ease, and explainability, and they have found Ultipa Graph DB's capabilities perfectly matching their needs. On the other hand, Ultipa's cloud-native development makes it 100% compatible with either public or private cloud deployment. It's projected that Ultipa SaaS (killer apps) will be released globally in late 2021.

The existing graph database market shows that graph database plays a crucial role in the fields of finance, e-commerce, social networking, communication, etc., understandably all of these fields are churning out big data and requiring deep and fast data processing capabilities. Gartner listed graph database as one of the top-10 data and analysis trends in 2019, 2020, and 2021, 3 years in a row! It is expected that the adoption of graph analytics and graph DBMSs will grow at 100 percent year over year through 2022, and 30% of the BI systems will be powered with graphs by 2023.