Graph Database (GDB for short) is a graph database product independently developed and controlled by Alibaba Cloud. It has been polished by rich application scenarios in Alibaba Group and has industry best practice experience.It is the fusion, analysis and decision engine of industry diversified heterogeneous data based on graph technology, and the best base of knowledge map.
Support attribute graph model, which is used to process highly connected data query and storage, and is real-time and reliable
Specifications
2-core 16G (stand-alone version)
storage space
twenty
Purchase duration
1 year
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Figure Database GDB High Availability Version
Support the integration, analysis and decision engine of multi heterogeneous data in the industry with a scale of one million
Specifications
8-core 64G
storage space
two hundred
Purchase duration
1 year
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Figure Database GDB
Support the integration, analysis and decision engine of multi heterogeneous data in the industry with a scale of 10 million
Specifications
16 core 128G
storage space
two hundred
Purchase duration
1 year
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Click Buy Now to get the latest price
Product advantages
Support standard diagram query language
Support Gremlin and Cypher languages, be compatible with mainstream map query products in the market, and reduce the development threshold
Real time online
Real time processing of massive data, analysis and insight of data value, and horizontal expansion of concurrent query performance through read-only nodes
Flexible architecture
Support Schema free to meet more flexible data architecture adjustment requirements
Automatic indexing
Automatically build indexes to optimize query efficiency and facilitate maintenance
Optimize the performance of super vertex query
GDB optimizes the query performance of super vertices by automatically building indexes
Support automatic machine learning
Native support docks with the automatic machine learning platform to gain insight into the laws of relational data through AI algorithms and generate intelligent decisions
Product Functions
With the help of graph database, we can build an industry knowledge map, so that your multiple heterogeneous data can produce more intelligent decisions.
Standard Drawing Query LanguageIt supports attribute graphs and is highly compatible with Gremlin and OpenCypher graph query languages.
Highly optimized self-developed engineHighly optimized self-developed graph computing layer and storage layer, cloud disk multiple replicas ensure super reliable data, and support the expansion of concurrency through read-only nodes.
High availability of servicesHigh availability instances are supported, node failure is quickly transferred, and business continuity is guaranteed.
Easy operation and maintenanceProvide backup recovery, automatic upgrade, monitoring alarm, failover and other rich operation and maintenance functions, greatly reducing operation and maintenance costs.
Based on the intelligent search recommendation algorithm and knowledge mapping technology of Dharma Institute, and integrating Alibaba e-commerce strategy precipitation, it provides enterprises with one-stop services through search and recommendation.It helps enterprises to quickly transition to the cold start process, customized solutions for business scenarios, and continuously improves core business indicators to achieve business revenue growth.
Capable of providing
Search and recommend one-stop service
Integrating search and recommendation to provide one-stop service, accurately understand users' intentions and provide a new intelligent recommendation to push users' thoughts.
Fusion of knowledge mapping technology and data precipitation
Using knowledge mapping technology, Alibaba e-commerce rich strategies and data precipitation are integrated to provide intelligent services driven by industry knowledge and covered by multiple scenarios.
Improve core business revenue indicators
User oriented business scenarios, through the empowerment of intelligent algorithms and strategies, and at the same time support the customized requirements of users for some business scenarios, to effectively improve the revenue indicators.
Graph based recommendation algorithm is an important technical direction in the current recommendation system. While taking into account the recommendation accuracy, it can also make the model have better interpretability.Through the common relationship discovery and analysis method of graphs, similar nodes are recommended by calculating the number of common neighbors.It is applicable to the commodity recommendation scenarios of e-commerce and insurance.
Capable of providing
Support standard diagram query language
It is compatible with the vast majority of open source map query products in the market, reducing the development threshold.
Real time online
Real time processing of massive data, analysis and insight into the value of data, to meet the needs of key business applications.
In a typical social network, there are often queries about "who knows who, who went to what school, who often lives where, and who likes what restaurants". Traditional relational databases are often inefficient or even unable to support queries over 3 degrees.The graph database natively supports the deep relationship query scenario of social recommendation, which can easily deal with the analysis and calculation of complex social network relationships.
Capable of providing
Schema free
Meet more flexible data architecture adjustment requirements.
Optimize super vertex query
Super vertices are tightly connected node clusters. Improper processing will slow down the performance of the graph database.For the super vertex problem, GDB is optimized through a specific index, which greatly improves the efficiency of super vertex query.
The traditional financial risk control model can collect the attribute feature information of various data sources, but it is difficult to mine the deep association between data sources.To mine the association characteristics of massive data in depth and quickly, using traditional methods will face great technical challenges.Through the graph representation learning technology, the topological information features in the knowledge map can be extracted as the input conditions of the risk control model and participate in the model training, which can help financial institutions build more accurate risk control models.
Capable of providing
Support automatic machine learning
Dock with the automatic machine learning platform, and gain insight into the laws of relational data through algorithms to generate intelligent decisions.
Schema free
Meet more flexible data architecture adjustment requirements.
In the financial scenario, it is particularly important for risk control whether the bonds held by creditors exceed the value of multiple guarantees of the collateral.The ring detection algorithm in the figure calculation is the core to find the closed-loop connection in the figure, which helps financial institutions find the deep relationship between collateral and creditors, so as to achieve the purpose of reducing risk control costs.
Capable of providing
Optimize super vertex query
Super vertices are tightly connected node clusters. Improper processing will slow down the performance of the graph database.For the super vertex problem, GDB is optimized through a specific index, which greatly improves the efficiency of super vertex query.
Schema free
Meet more flexible data architecture adjustment requirements.
There are gang crime scenes on many platforms, such as gang credit card cash out, wool party, and even gang illegal and criminal activities.The core feature of gang crime is that its members have certain relationships, or their behaviors have some similar characteristics.By combining graph with machine learning, the topological relationship information in the group relationship map is extracted, and the known group information is used as the sample to train the machine learning model, classify the target nodes, or predict their relationships.
Capable of providing
Automatic indexing
Automatically build indexes to optimize query efficiency and facilitate maintenance.
Real time online
Real time processing of massive data, analysis and insight into the value of data, to meet the needs of key business applications.
The development of transactions, such as electronic payment and mobile payment, has also brought more serious transaction security problems.In order to prevent economic losses caused by illegal financial acts, the application of anomaly detection algorithm in the field of online financial transactions is used to accurately identify abnormal transactions in online financial transactions and prevent illegal financial acts in a timely manner.Through the graph database, identify the device information, payment environment information, transfer information, and social information of payment users, detect possible abnormal risks, and improve the security of payment.
Capable of providing
Support automatic machine learning
Dock with the automatic machine learning platform, and gain insight into the laws of relational data through algorithms to generate intelligent decisions.
Support standard diagram query language
It can be compatible with mainstream map query products in the market, reducing the development threshold.
Alibaba Cloud Image Database - Public beta release of new products
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2019-09-30 New Features
Alibaba Cloud map database GDB supports Gremlin map query language
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New functions on October 25, 2019
GDB supports dataworks and can import data from MySQL, ODPS, OTS, etc. to GDB
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2019-10-31 experience optimization
Index function enhancement: support point center index, add support composite condition index function
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New functions on December 25, 2019
Support Go client, release v1.0 version
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New region/zone on December 26, 2019
Open service in Indonesia (Jakarta) region
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2020-02-17 New Region/Availability Zone
Figure GDB opened in Qingdao and Hong Kong
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New products on February 26, 2020
Figure Commercial launch of database GDB
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2020-04-08 New Features
Figure Database GDB instance type supports configuration reduction
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2020-06-29 New Features
AliCloud map database GDB is compatible with OpenCypher map query language
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2020-06-29 new version/new specification
AliCloud map database GDB supports the single node specification, which is used for testing, learning and other scenarios that do not require high availability
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New functions of 2020-07-01
Alibaba Cloud image database GDB is deeply integrated with ElasticSearch to provide word segmentation retrieval function
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2020-07-16 New Region/Availability Zone
Service opening in India (Mumbai) region
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2020-12-19 new version/new specification
Alibaba Cloud Image Database Products Officially Launched on the VPC Enterprise Edition
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2021-01-23 New Features
GDB read-only node function officially released throughout the network
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2021-01-28 New Features
GDB diagram database supports the function of setting security groups
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2022-03-08 New Features
Figure Automatic machine learning component release of database
