Understanding the complexity of live pig trade organization is a key factor to predict and control major infectious diseases such as Classical or African swine fever. Whereas the organization of pig trade has been described in several European countries with indoor commercial production systems, little information is available on this organisation in other systems like outdoor or small-scale systems. The objective of this study was to describe and compare the spatial and functional organisation of live pig trade in different European countries and different production systems. Data on premise characteristics and pig movements between premises were collected during 2011 from Bulgaria, France, Italy and Spain, which swine industry is representative of most of the production systems in Europe (i.e. commercial vs small-scale; outdoor vs indoor). Trade communities were identified in each country using the Walktrap algorithm. Several descriptive and network metrics were generated at country and community level. Pig trade organization showed heterogeneous spatial and functional organization. Trade communities mostly composed of indoor commercial premises were identified in Western France, Northern Italy, Northern Spain and North-Western Bulgaria. They covered large distances, overlapped in space, demonstrated both scale-free and small-world properties, with a role of trade operators and multipliers as key premises. Trade communities involving outdoor commercial premises were identified in Western Spain, South-Western and Central France. They were more spatially clustered, demonstrated scale-free properties, with multipliers as key premises. Small-scale communities involved the majority of premises in Bulgaria and in central and Southern Italy. They were spatially clustered and had scale-free properties, with key premises usually being commercial production premises. These results indicate that a disease might spread very differently according to the production system and that key premises could be targeted to more cost-effectively control diseases. This study provides useful epidemiological information and parameters that could be used to design risk-based surveillance strategies or to more accurately model the risk of introduction or spread of devastating swine diseases such as African swine fever, classical swine fever or foot-and-mouth disease.