What's SuperMap SDX+?

SuperMap Spatial Database eXtension (SuperMap SDX+) is a built-in spatial and attribute data operating engine that is distributed with each SuperMap product. Unlike ESRI's ArcSDE, SuperMap SDX+ is not a separated GIS product. The benefits from this design are listed in the table below:

SuperMap SDX+ provides geospatial database accessing, including storing data, building index, reading and updating spatial data, and etc. Most of SuperMap products, for example, SuperMap Deskpro, SuperMap Objects, and SuperMap IS .NET, contain SuperMap SDX+, can manage spatial data with DBMS internally.

Both Data storing and processing are critical for the GIS application performance. With years’ research and improvement, SuperMap SDX+ has become a more reliable, powerful, and higher efficient geospatial database eXtension. The spatial data and its attribute data can be saved integratively into various relational databases; the varieties of maintenance work, for example, index, appending, updating, and deleting operations can be carried out easily. The data query can be performed based on either attribute or spatial condition to return the required data. In addition, many advanced functions such as long transaction, versioning and topological relationship maintenance are also provided.

SuperMap SDX+ supports most of the popular commercial databases, such as Oracle, SQL Server, Sybase, DB2 and etc., therefore, multi-node cluster can be built among homogenous database while the distributed clusters can be created on the heterogeneous databases and operating systems. Moreover, SuperMap SDX+ is developed with the standard C++ programming language, this makes cross platform development possible so that the flexible spatial data accessing and managing can be achieved on many operating systems (including Linux, UNIX etc.).

Figure 1 SuperMap SDX+ spatial database eXtension

Technical Features

This is a trend for GIS to use large relational databases for integral management of spatial data and its attribute data. Spatial database technique has its advantages in many aspects as follows: Massive data management capability, integral storage of spatial data and attribute data, multi-user concurrent access (read & write), complete access permission control and data security mechanism.

More and more large-scale and middle-scale GIS projects take the spatial database technology as the solution for storing and managing the spatial data. As a very important part of SuperMap GIS software, SuperMap SDX+ adopts the advanced spatial database storage technology, indexing technology, and query technology to implement "integrating spatial and attribute data", "integrating vector and raster data" and "integrating spatial information and business information", therefore, SuperMap GIS products are qualified for supporting the large-scale GIS projects.

Three outstanding features of SuperMap SDX+, proved by a series of customer's applications and tests, are:

　　◆ Easy installation and usage with full database technology.
　　◆ High performance of massive data accessing and managing.
　　◆ Perfect data model sufficing the requirements of various large GIS applications.

Easy Installation and Deployment

　　◆ Easy configuration

Since SuperMap SDX+ is built in each SuperMap GIS product, it does not require any configuration on the complex spatial database servers, when deploying a GIS application developed with SuperMap Objects, the SuperMap SDX+ engine is installed on the customer's machine automatically. Because SuperMap SDX+ adopts all standard database operations, any developer and DBA, who have some database knowledge, can manage the spatial database.

The DBMS's database management procedure provides data security control and data permission control to avoid the potential security vulnerability. Accessing to a database via the standard database protocol can smooth the data exchange over the web server. The more important thing is that SuperMap SDX+ manipulates database via the standard SQL syntaxes so that the database server performance can be fully leveraged and the users on client side can perform both query and maintenance tasks with the standard database procedures.

　　◆ Full support for popular commercial relational databases

SuperMap SDX+ fully supports most commercial relational database, including Oracle, Oracle Spatial, SQL Server, DB2, Sybase, native DM, and Kingbase.

SuperMap SDX+ has encapsulated the interfaces for accessing those databases transparently, therefore, the users do not need to know what kind of server, operating system, or database type. The data accessing and managing, through the similar interfaces, can reduce the difficulty of database configuration, development, and application.

　　◆ Support for Oracle RAC

RAC (Real Application Cluster) is one of the key functionalities of Oracle database 10g Enterprise Edition. It allows a database to be installed across multiple servers. RAC technology perfectly solves two fundamental problems: Firstly, the other servers can automatically take over the tasks from a server that is broken down; Secondly, the more important thing is that all servers within the clusters concurrently enhance the capability of handling the requests received from client sides.

In January, 2005, SuperMap, Oracle and HP performed the compatibility tests for SuperMap GIS products with Oracle 10g and Unix/Linux systems. The testing results show that SuperMap SDX+ has a perfect compatibility with Oracle 10g on Unix/Linux platform and fully supports the most advanced RAC technology of Oracle 10g. SuperMap GIS products can be applied to the large-scale GIS applications with the reliable and higher performance services.

Figure 2 Oracle RAC technology

High Performance of Massive Spatial Data Accessing and Managing

　　◆ Hybrid multilevel indexing technique

Indexing is a key technique in the spatial database engine. It directly affects the efficiency of data access and query. However, any indexing technique has its own disadvantage, hence, no single indexing technique can satisfy the requirements of data access to hybrid storage model of massive image data and vector data. SuperMap comes up with hybrid multilevel indexing technique - combining multi-layer grid, quad tree and R tree indexing methodologies. This technique can provide high efficiency of data processing.

For the standard grid spatial data, SuperMap also provides creating library index according to the specified field or spatial extent. Using this index with the file cache technique can provide incredible access ability.

Moreover, SuperMap SDX+ allows users to maintain the index of the attribute data, including creating and deleting attribute field index. This helps speed up query and access to the attribute data.

　　◆ File cache technique

File cache provides an intelligent distributed storage scheme for balancing the load of the server and improve overall performance. With enabling this file cache option, the local cache is firstly searched to see if it is the latest data when an application intends to access the data in the spatial database. If there is no related cache file or the cached data is not the latest one, the required data will be retrieved from the server to update the local cache that can be used next time; If the latest version of the required data is available in local cache, the data browsing and analyzing is performed with the local cache without requesting data from the server. Through this scheme, the server and network load can be tremendously reduced and the overall performance is greatly improved.

In order to save disk space and increase flexibility, no spatial index is built within the file cache. Therefore, it is not recommended to enable file cache for a dataset that has huge amount of records. But this situation can be resolved by combining the file cache with the library index. I.E. the data, having library index built, can be loaded into the file cache. This method will reduce the cache size and ensure the large data processing performance.

The file cache mechanism will occupy the disk space on client-side machine. SuperMap SDX+ employs highly efficient compression algorithms to reduce the space occupied by the cache file; On the other hand, the LRU algorithms is used to control the total possible size occupied by the cache.
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　　◆  Lossless and lossy data compression

With the development of new data acquisition technology, the increased temporal and spatial resolution of GIS data and data volume affect data storing space, data processing, and the data transmission rate on the fixed network bandwidth. Data compression is an efficient way to resolve this problem. Additionally, it can improve data security during communicating through the network.

SuperMap SDX+ employs both lossless and lossy data compression techniques for vector and raster data. Lossless data compression is a class of data compression algorithms that allows the exact original data to be reconstructed from the compressed data. As the compression rate is limited by the statistical redundancy, therefore, the rate is usually from 2:1 to 5:1. Due to the limitation of compression rate, this compression is used for industries or applications with demand for high precision data rather than for massive spatial data storage and transmission.

In order to obtain higher compression rate, SuperMap SDX+ provides lossy data compression for vector and raster data. This technique can implement much more compression rate comparing to lossless data compression. Although not all original data can be restored after being decompressed, the lost data has very little effect on the data precision. Therefore, it is used widely in most GIS projects. It needs to be mentioned that the lossy data compression technique for vector data differs from that for raster data. The compression for vector data takes the advantage of the adjacent relationships between vertices of spatial objects to perform the frequency division encoding on each coordinates; while the one for raster data is similar to compress image in multimedia applications by using Run-Length Encoding, Discrete Cosine Transform, and wavelet transform.
The built-in compression technique can intelligently adjust the compression parameters according to the features of spatial data. It had been proved practically that SuperMap's compression technique can reduce the compression procedures and promise the high compression rate and efficiency.