Sql Server Data Types Examples – There are two types of spatial data. The geometry data type supports planar or Euclidean (flat earth) data. The geometry data type conforms to
Version 1.1.0 and is compatible with SQL MM (ISO standard). SQL Server also supports the geographic data type, which stores ellipsoidal (round-Earth) data such as latitude and longitude GPS coordinates.
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SQL Server spatial tools is a collection of open-source tools sponsored by Microsoft for use with spatial types in SQL Server. This project provides a set of reusable functions that applications can use. These functions may include data conversion routines, new transformations, aggregates, etc. See Microsoft/SQLServerSpatialTools on GitHub for more details.
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The geometry and geography data types support 16 types of spatial data objects or instance types. However, only 11 of these court types are
; you can create and work with these instances (or instantiate them) in a database. These instances derive certain properties from their parent data types.
The figure below shows the geometry hierarchy on which the geometry and geography data types are based. Instantiable geometry and geography types are indicated in blue.
There is an additional instantiable type for the geographic data type: FullGlobe. Geometry and geography types can recognize a given instance as long as it is a well-formed instance, even if the instance is not explicitly defined. For example, if you define a Point instance explicitly using the STPointFromText() method, geometry and geography recognize the instance as a point, as long as the method’s input is well-formed. If you define the same instance using
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The two types of spatial data often behave similarly. There are some key differences in how data is stored and handled.
The defining data for LineString and Polygon types are vertices only. The connecting edge between two vertices in a geometry type is a straight line. However, the connecting edge between two vertices in a geography type is a short large elliptic arc between the two vertices. A great ellipse is the intersection of the ellipsoid with a plane through its center. A major elliptic arc is an arc segment on the major ellipse.
Arc segments for geometry types are defined on the XY Cartesian coordinate plane (Z values are ignored). Arc segments for geography types are defined by curve segments on a reference sphere. Any parallel on the reference sphere can be defined by two complementary circular arcs where the points for both arcs have a constant angle of latitude.
In the planar (flat earth) system, measurements of distances and areas are given in the same unit of measurement as coordinates. Using the geometry data type, the distance between (2, 2) and (5, 6) is five units, regardless of the units used.
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In an ellipsoidal or round system, coordinates are given in degrees of latitude and longitude. However, lengths and areas are usually measured in meters and square meters, although the measurement may depend on the spatial reference identifier of the geographic instance. The most common unit of measurement for the geographic data type is meters.
In an ellipsoidal system, a polygon without orientation is meaningless or ambiguous. For example, does a ring around the equator describe the northern or southern hemisphere? If we use the geography data type to store the spatial instance, we must specify the orientation of the ring and describe precisely the location of the instance.
The interior of the polygon in an ellipsoidal system is defined by the “left rule”: if you imagine walking along the ring of a geographic polygon, following the points in the order in which they are listed, the area on the left is treated as the interior of the polygon, and the area on the right as the exterior of the polygon.
When the compatibility level is 100 or lower in SQL Server, then the geographic data type has the following restrictions:
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In SQL Server, FullGlobe is a special type of polygon that covers the entire globe. It has an area, but no boundaries or vertices.
Discusses outer rings and inner rings, but this distinction does not make sense for the SQL Server geographic data type; any ring of a polygon can be considered as the outer ring.
Three instantiable types can take circular arc segments: CircularString, CompoundCurve, and CurvePolygon. A circular arc segment is defined by three points in a two-dimensional plane, and the third point cannot be the same as the first point. Some examples of circular arc segments:
The first two examples show typical circular arc segments. Notice how each of the three points is on the perimeter of a circle.
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Two other examples show how a line segment can be defined as a circular arc segment. Three points are still required to define the circular arc segment, unlike a regular line segment, which can be defined by only two points.
Methods that operate on circular arc segment types use straight line segments to approximate the circular arc. The number of line segments used to approximate the arc will depend on the length and curvature of the arc. Z values can be stored for each of the circular arc segment types, but will not be used in calculations.
If Z values are given for arc segments, then they must be the same for all points in the arc segment for it to be accepted for input. E.g:
Notice that a CircularString instance requires seven points to define the triangle. The LineString instance only requires four points to define the triangle. The reason for this is that a CircularString instance stores circular arc segments and not line segments. The sides of the triangle stored in the CircularString instance are ABC, CDE, and EFA. The sides of the triangle stored in the LineString instance are AC, CE, and EA.
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CircularString instances use fewer points to store curve boundaries with greater precision than LineString instances. CircularString instances are useful for storing circular boundaries, such as a 20-mile search radius from a given point. LineString instances are good for storing boundaries that are linear like a square block.
In the examples above, either a LineString instance or a CompoundCurve instance could store the figure. This next example uses a CompoundCurve to store a slice of pie:
A CompoundCurve instance can directly store the circular arc segment (2 2, 1 3, 0 2), but a LineString instance should convert the curve into several smaller line segments.
Storing the pie slice using a CircularString instance requires using three points for each line segment. If an intermediate point is not known, it must either be calculated or the end point of the line segment must be doubled, as shown in the following excerpt:
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CompoundCurve instances allow both LineString and CircularString components, so only two points to the line segments of the pie section are known. This code example shows how to use a CompoundCurve to store the same figure:
CurvePolygon instances can use CircularString and CompoundCurve instances when defining their outer and inner rings. The polygon courts cannot. So you build a software application. One of the first issues to address is how to store your data. Which database will you choose?
A database management system, or DBMS, is a type of software that communicates with the database itself, applications, and user interfaces to obtain data and analyze it. The DBMS also contains the key tools to govern the database.
For our comparison, we chose the 10 most used database management systems: MySQL, MariaDB, Oracle, PostgreSQL, MSSQL, MongoDB, Redis, Cassandra, Elasticsearch and Firebase. Focusing on their business benefits and challenges, we’ll also present the best use cases for each.
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Since databases are only one part of the overall data management strategy, learn about this comprehensive approach in our dedicated article.
Basically, there are two types of DBMS: relational and non-relational, also called SQL and NoSQL respectively. Before discussing the most popular database options, let’s take a closer look at how relational and non-relational database systems differ by considering commonly used data structures, performance, scalability, and security .
A relational database is a type of data warehouse that organizes data into tables that are linked together, which explains the name. Structured Query Language is the core of these systems, as it is used to communicate and manage these databases, giving rise to the second name – SQL databases. RDBMSs have a predefined schema, which means that data resides in rows (records) and columns (attributes) with a strict structure. Here, each record typically holds a value for each attribute, resulting in clear dependencies between different data points.
Scalability. Relational databases typically scale out, meaning that the data lives on a single server, and scaling is achieved by adding more computing (CPU, GPU, and RAM) to that server. However, moving from small to larger machines often involves downtime. Scaling an SQL database across multiple servers (horizontal scaling) can be challenging because it requires changes to the data structure and additional engineering efforts.
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Performance. Relational databases show excellent performance with intensive read/write operations on small and medium datasets. They also provide improved data retrieval speed by adding indexes to data fields to query and join tables. However, when
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