Lindorm Ganos is a native extension of the Lindorm wide table engine (LindormTable). It is compatible with the APIs of SQL, GeoMesa, and streaming engines. By using Lindorm Ganos, you can efficiently store, query, and analyze spatio-temporal data based on Lindorm wide tables. If you need to analyze and process spatio-temporal trajectories in your business, we recommend that you activate the Lindorm Ganos feature.
Background information
Large amounts of spatio-temporal trajectory data is generated in various scenarios, such as travelling, Internet of Vehicles (IoV), Internet of Things (IoT), autonomous driving, logistics, and the geographic information system (GIS). Users need to use the spatio-temporal trajectory data to query spatio-temporal ranges, determine geofences, or perform data mining. For example, users can use spatio-temporal trajectory data to query the vehicles that have passed through an area within a specified period of time, monitor whether a vehicle deviates from the planned route in real time, or query all vehicles that are 500 meters around the current location.
Lindorm Ganos acts the similar role as the PostGIS extender in PostgreSQL and the geographic range query feature in MongoDB. Lindorm Ganos supports standard geometry objects and provides spatio-temporal indexes for efficient queries on spatio-temporal data. In addition, Lindorm Ganos can provide high throughput and scalability with low storage costs. Therefore, Lindorm Ganos is a cost-effective solution for you to process spatio-temporal trajectory data.
Supported interfaces
Lindorm Ganos supports the interfaces of SQL, GeoMesa, and streaming engines.
Category | SQL interfaces | GeoMesa interfaces | Streaming engine interfaces |
Supported interfaces | Standard SQL interfaces | GeoTools APIs or ECQL interfaces | Standard Flink SQL interfaces |
Features |
| Inherits the features of open source GeoMesa. |
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Performance | Lindorm Ganos SQL is superior to open source GeoMesa in performance because Lindorm Ganos SQL adopts a variety of technologies such as query rewrite, parallel queries, shards, and optimized spatial approximation algorithms. | Lindorm Ganos GeoMesa is superior to open source GeoMesa and HBase in performance. | Lindorm Ganos for streaming engines offers excellent query performance by providing technologies such as in-memory indexes and parallel queries. |
Orientation | Lindorm Ganos SQL is applicable to applications that use SQL interfaces such as PostGIS or the spatial-temporal features of GeoMesa, MongoDB, and Redis. | Lindorm Ganos GeoMesa is applicable to applications that use open source GeoMesa. | Lindorm Ganos for streaming engines is applicable to the migration of spatio-temporal applications that use streaming engines such as Flink and Spark. |
Lindorm Ganos SQL
Features
The following table describes the features supported by Lindorm Ganos SQL.
Feature | Description |
Standard spatial data types such as points, line strings, and polygons | Lindorm Ganos SQL supports point, LineString, and polygon objects. For more information, see Spatial data types. |
Standard SQL syntax |
For more information about the SQL syntax supported by Lindorm Ganos SQL, see DDL and DML. |
Common spatio-temporal functions |
For more information about other spatio-temporal functions, see Overview. |
Spatio-temporal primary key index | Spatio-temporal primary key indexes can be used to accelerate spatio-temporal queries in which only spatial ranges or spatial and time ranges are specified as conditions.
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Spatio-temporal secondary index | Spatio-temporal secondary indexes can be used to accelerate spatio-temporal queries in which only spatial ranges or spatial and time ranges are specified as conditions.
Note You do not need to create a redundant replica for spatio-temporal data because Lindorm Ganos SQL supports spatio-temporal secondary indexes. |
Features provided by LindormTable |
For more information about the features provided by LindormTable, see Developer Guide. |
Scenarios
Lindorm Ganos SQL is applicable to manage and query spatio-temporal data in traveling, navigation, aviation, Internet of Vehicles (IoV), and logistics scenarios. The following table describes the common scenarios of Lindorm Ganos SQL.
Scenario | Example |
The storage and query of trajectory data |
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Geographic grid aggregation |
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Real-time geofencing |
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Location-based services | Search for the information about restaurants five kilometers around the current location. |
Lindorm Ganos GeoMesa
Lindorm Ganos GeoMesa is compatible with open source ecosystems such as GeoMesa and GeoServer and can be used to store, query, analyze, and mine spatial or spatio-temporal data.