Data editing and management system (Windows/Linux)

The data editing and management system pattern is typically deployed to Windows and Linux using the ArcGIS Enterprise on Windows and Linux software.

ArcGIS Enterprise for Windows and Linux includes several components that span the data, services/logic, and presentation tiers, and work together to provide a complete system. ArcGIS Enterprise on Windows and Linux is fully supported on virtual environments (running a supported operating system), as well as cloud providers running virtual machines that meet the system requirements. Esri also provides deployment tooling for cloud platforms including Amazon Web Services (AWS) and Microsoft Azure.

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Base architecture

The following is a typical base architecture for a data editing and management system deployed on Windows or Linux.

This diagram should not be taken as is and used as the design for your system. There are many important factors and design choices that should be considered when designing your system. Review the using system patterns topic for more information. Additionally, the diagram depicted below delivers only the base capabilities of the system; additional system components may be required when delivering extended capabilities.

Data editing and management system base architecture (Windows/Linux)

Key components of this architecture include:

  • Enterprise geodatabases are commonly used in data editing and management systems for persisting user-managed (editable) data. Enterprise geodatabases are information models that add functionality to relational database management systems (DBMS). The enterprise geodatabase supports advanced data models, as well as advanced data editing and management capabilities such as support for a long transaction model.
  • A base deployment of ArcGIS Enterprise, including the ArcGIS Data Store, ArcGIS Server, and Portal for ArcGIS. The ArcGIS Data Store can be used for persisting ArcGIS-managed (editable) data. The ArcGIS Web Adaptor component of ArcGIS Enterprise is also recommended and may be required in some situations.
  • ArcGIS Server, specifically the GIS Server role, which delivers editable feature services for data stored in the enterprise geodatabase. The ArcGIS Server providing enterprise data services is depicted as a logically distinct component of this system from the ArcGIS Server that provides hosted and utility services (and that completes the base deployment described above). This is because they play two different roles in the system and are often designed and deployed separately at a physical level. The ArcGIS Web Adaptor component of ArcGIS Enterprise is also recommended and may be required in some situations.
  • ArcGIS Online, Esri’s SaaS infrastructure, which typically provides basemaps (for example, a satellite map), reference data (such as places), as well as other location services (including geocoding and search) for this system. Alternatively, it is possible for the organization to host and manage their own location services instead of using Esri’s SaaS system. See the location services system pattern for more information.
  • There are several applications commonly used in this pattern. Learn more about applications used in data editing and management systems.

Key interactions in this architecture include:

  1. Client applications communicate with enterprise data services as well as location services over HTTPS, typically via stateless REST APIs. This pattern makes heavy use of feature services for editing specifically, though several other service types are also typically used.
  2. ArcGIS Server maintains persistent TCP connections to both the database management system (DBMS) hosting the enterprise geodatabase as well as the ArcGIS Data Store. The former requires that appropriate database client software be installed on the ArcGIS Server machines communicating with the DBMS.
  3. ArcGIS Monitor, recommended for monitoring and optimizing the GIS system components, communicates with a variety of ArcGIS and IT (e.g., DBMS) components using a variety of mechanisms. See ArcGIS Monitor documentation for more information.
  4. References to location services hosted and managed by ArcGIS Online (such as basemaps) are typically registered and made available for use within ArcGIS Enterprise. Some services are referenced automatically when installing ArcGIS Enterprise, though additional sharing of content and services between these two systems can be performed manually or automatically. See configuring ArcGIS Online utility services, configuring ArcGIS Living Atlas content, and distributed collaboration.

ArcGIS License Manager may be required for configuring and managing ArcGIS Pro licenses. See ArcGIS License Manager documentation for more information.

Additional information on interactions between ArcGIS Enterprise components can be found in the ArcGIS Enterprise on Windows and Linux product documentation, including a diagram of ports used in an ArcGIS Enterprise on Windows and Linux deployment.


The capabilities of the data editing and management system on Windows and Linux are described below. See the capability overview and comparison of capability support across deployment patterns for more information.

Capabilities used in a data editing and management system, but typically provided by other systems, such as basemaps, geocoding, and other location services provided by a location services system are not listed below. Learn more about related system patterns.

Base capabilities

Base capabilities represent the most common capabilities delivered by data editing and management systems and that are enabled by the base architecture presented above.

Extended capabilities

Extended capabilities are typically added to meet specific needs or support industry specific data models and solutions, and may require additional software components or architectural considerations.


The considerations below apply the pillars of the ArcGIS Well-Architected Framework to the data editing and management system pattern on Windows and Linux. The information presented here is not meant to be exhaustive, but rather highlights key considerations for designing and/or implementing this specific combination of system and deployment pattern. Learn more about the architecture pillars of the ArcGIS Well-Architected Framework.


Reliability ensures your system provides the level of service required by the business, as well as your customers and stakeholders. For more information, see the reliability pillar overview.

  • Data integrity and recoverability is paramount
  • SLAs requiring high levels of availability are common
    • High availability and fault tolerance is achieved through redundant infrastructure at all system tiers.
    • Disaster recovery is less common, but possible.

Learn more about minimizing data loss and downtime in ArcGIS Enterprise.


Security protects your systems and information. For more information, see the security pillar overview.

  • Authentication and authorization are almost always required, apart from a crowd sourcing style collection scenario (though these are more commonly deployed using SaaS or PaaS).
  • Access control is possible, and frequently implemented, at all system tiers.
    • Advanced, fine-grained access control such as row or column-level security is typically achieved using Server Object Interceptors and/or partner solutions.
  • Auditing is very common, and is typically implemented using editor tracking.

Explore the ArcGIS Enterprise Hardening Guide to learn about strategies and associated settings that can be implemented to improve the security posture of ArcGIS Enterprise deployments.

Performance & scalability

Performance and scalability aim to optimize the overall experience users have with the system, as well as ensure the system scales to meet evolving workload demands. For more information, see the performance and scalability pillar overview.

  • SLAs requiring high performance are common
    • Database performance is typically a major factor in overall system performance
    • Data model complexity may also impact system performance
    • High performing, low latency networks are typically required
  • Editing performance is key, as even marginal performance degradation may negatively impact the user experience and overall workforce productivity.
  • Scaling up/down and out/in is typically directed and/or reactive, as in most cases the userbase is well known and the demands on the system evolve predictably.


Automation aims to reduce effort spent on manual deployment and operational tasks, leading to increased operational efficiency as well as reduction in human introduced system anomalies. For more information, see the automation pillar overview.

  • Workflow automation is common, especially with large groups of editors working in concert to edit and maintain shared or related datasets. See ArcGIS Workflow Manager for more information on this extended capability.
  • Data management typically involves moderate-to-heavy use of automation, often leveraging Python scripting to perform repeatable tasks or reporting on the enterprise geodatabase. See the ArcGIS API for Python for more details.
  • System administration automation, including software deployment automation, infrastructure as code, and DevOps, is also commonly employed.


Integration connects this system with other systems for delivering enterprise services and amplifying organizational productivity. For more information, see the integration pillar overview.

  • Integration with other information systems such as Enterprise Asset Management (EAM), Customer Relationship Management (CRM), and Computer-Assisted Mass Appraisal (CAMA) systems is common.
  • Data exchange and alignment between systems is very typical
    • Use of ArcGIS APIs and SDKs is quite common
  • 3rd party integration tools and applications are also available


Observability provides visibility into the system, enabling operations staff and other technical roles to keep the system running in a healthy, steady state. For more information see the observability pillar overview.

  • Successful operation of data editing and management systems typically benefits from a good understanding of how data is being edited and by whom. This may include, but is not limited to, who is editing what, the nature of those edits, the nature of edit transactions, use of batch editing capabilities, as well as the overall volume and cadence of edits. Management and monitoring of feature services is especially important, including use of edit tracking and auditing. Monitoring at the enterprise geodatabase level is also critical, especially when moderate-to-large teams of editors are involved. Learn more about creating and maintaining enterprise geodatabases.
  • Feature service webhooks can be employed for observability purposes.
  • ArcGIS Enterprise on Windows/Linux can be observed in a variety of ways including server logs and server statistics. Monitoring of system availability, performance, and usage is most critical to this system pattern. In addition to monitoring the ArcGIS Enterprise software, it is important to monitor all supporting components and infrastructure such as the Windows or Linux operating system, databases and other data stores, as well as compute, network, security, and other infrastructure. Learn more about monitoring system performance.
  • Some extended capabilities of this system pattern, such as workflow management and automation with ArcGIS Workflow Manager, have additional observability support. Review the corresponding product documentation for more information.
  • Use of web analytics may also be helpful for editing using custom web-based applications.
  • Additional observation of user logins and account changes may be possible through the configured identity provider when using SAML and/or OpenID Connect logins.


Additional considerations for designing and implementing a data editing and management system on Windows and Linux include:

  • Successful operation requires strong understanding of GIS, IT, and database concepts as well as technology. This includes knowledge and skills specific to the selected database management system (DBMS).
  • Data governance and alignment with IT policies and roles, such as data steward and database administrator, should strongly be considered when implementing this system pattern.

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