SDMX is designed for statistics.
SDMX provides a structured and standardised way to describe statistical data in any domain, and a common language for exchanging both the data and its structural metadata between organisations and systems (information about how the data is or should be structured).

It allows statisticians to robustly describe the structure and rules for complex datasets, provides data providers with a clear description about what the data should look like, and data users with an unambiguous understanding of how to interpret it.

SDMX is a proven, open, non-proprietary standard sponsored by seven international organisations including the World Bank, the International Monetary Fund and the United Nations Statistics Division. It's also an International Standard ISO 17369:2013.

SDMX-ML v1.0, v2.0 and v2.1
Data sub-formats: v2.0 Generic, v2.0 Compact, v2.1 Generic, v2.1 Structure Specific
SDMX-EDI
SDMX-JSON 1.0 (data and structures)

SDMX 3.0 will be supported when it is released.

No
All Fusion Registry variants are closed source.

However, if you're a central bank or international organisation user of the Enterprise Edition, you'll get access to the source code if you need it.

Yes

There are now two free versions: Fusion Registry Community Edition which is an SDMX metadata registry, and Fusion Registry Data Essentials which does the same as the Community Editon, plus all of the essential functions for loading, integrating, storing, processing and publishing aggregated statistical data using the SDMX standard.

The Community Edition is free for anyone to download and use. Fusion Registry Data Essentials is free for qualifying organisations.

There's more here.

Pricing information for the paid-for commercial editions can be found here.

As a 'structural metadata registry', its fundamental purpose is to act as a controlled source of metadata for other applications and processes that do handle data. For instance, an application for reporting data to another organisation like the IMF could query a Registry for up-to-date details about how the data should be structured and classified. This is an example of a 'metadata-driven process'.

The Community Edition can also be used as an interactive tool for authoring and maintaining structural metadata through its web user interface.

Register here to download.

Structural Metadata is information about how the data should be structured in terms of its dimensionality, the concepts being measured and how they are classified.
SDMX provides a range of 'structural metadata artefacts' including Concept (e.g. frequency, country, gender), Codelist (classifications) and Data Structure Definition (describing the dimensionality of a particular dataset).
Statisticians use structural metadata artefacts to define their statistical data model in Fusion Registry in the same way that a SQL database administrator will use tables, columns and keys to define the schema for a relational database.
While a Data Structure Definition (DSD) sets out the structure or dimensionality of a dataset, a Dataflow describes a specific instance. For instance, a DSD for National Accounts could be used for GDP, Central Government Debt and CPI Dataflows - different datasets that all share the same dimensionality. Data consumers retrieve the data they are interested in by querying the relevant Dataflow. In some ways, Dataflows are equivalent to Tables in the SQL relational model.
Structural metadata is also used to describe rules to be applied when collecting and processing data. In particular, Content Constraints set what data a provider is authorised to report.

Reference Metadata (also called Referential Metadata) is human-readable information that can be attached to datasets, series, observations, concepts and other data and structural metadata elements. If you want to provide some explanatory notes to help users interpret a dataset, Reference Metadata is the thing to use. And it's not just restricted to text. Reference Metadata can be plain text, HTML or links to other documents and resources such as videos and images.

Time Series: Yes
Fusion Registry is designed primarily for aggregated time series.

Cross Sectional: Partial
Fusion Registry can model cross sectional data and manage it to an extent. However, many functions assume the presence of a time dimension so the best approach is to model cross sectional datasets with a time dimension, but give all observations the same survey time.

No: only aggregated data at present.
This is parimarily a limitation of the current 2.1 version of SDMX which is mainly concerned with aggregated data. Better support for microdata is planned in the forthcoming SDMX 3.0 information model including alternative measure cardinality on Data Structure Definitions, and more relaxed Codelists that don't need to comply with the current strict rules imposed by the standard.

No: not at present.
VTL 2.0 support is on the development roadmap.

Yes: using Metadata Technology's Time Series Expression Language.
Fusion Registry's time series calculation engine executes formulas in expressed in Metadata Technology's Time Series Expression Language on existing series in its statistical data repository to create new series. In this sense it follows the functional programming paradigm where the series / datasets referenced by an expression are immutable, and the result is always new series.

• Transformation - SDMX Structure Maps can be used to transform data to different structures and classification schemes.
• Calculation - Calculate new series using Metadata Technology's Time Series Expression Language.
• Format Conversion - Convert data between formats including SDMX formats, non-SDMX formats like Excel.
• Aggregation - Aggregate series to a higher level using definable functions.
• Frequency Conversion - Convert time series to different frequencies using definable re-sampling and interpolation functions.
• Structural Validation - Check data for compliance with the information model defined by the SDMX structural metadata. This can also check for other potential problems such as duplication observations.
• Semantic Validation - Check data for compliance with definable business rules such as observations for individual classifications match the value reported for TOTAL.

Fusion Registry does not have a workflow engine so has no built-in way for users to define and execute processes consisting of sequences of tasks.
However, third party workflow tools can be easily integrated using Fusion Registry's rich REST API to execute tasks and receive results.
Shell scripts (.sh, .bat and Windows Powershell) can also be created using Fusion Command Line Interface allowing certain tasks such as loading data and metadata to be scripted.

No
Although all functions can be executed using the REST API, so tools like Postman or Curl can be used instead.

Registry Content: Yes
Registry content (names, labels, descriptions etc) can be loaded, displayed and retrieved in multiple languages, including those written right-to-left such as Arabic and Hebrew. Users can choose their preferred language - content will be displayed in that language if available, or the default language otherwise. The default is often English, but it doesn't need to be.

Fusion Registry Web User Interface: No
Text on Fusion Registry's web user interface - including the menu bar, buttons and informational messages displayed for various reasons - are always in English.

Fusion Data Browser Web User Interface: Yes
Legends, buttons, menu items and other text can all appear in a language of a your choice using configurable language translation JSON files.

Fusion Registry is a Java web application so it will run on any computing platform with a Java run-time environment and a suitable Java web application server such as Apache Tomcat. It has a web user interface so users require only a standard web browser.

It's also designed to be very scalable, so can be run on most computers and servers with a minimum of 4GB of memory for the Community Edition. 8GB is recommended for the Enterprise Edition. More memory and processing capacity will be required depending on the volume of data and usage. There's more on this in the What are the system requirements? section.

Fusion Registry provides a comprehensive REST web services API for integration with other systems. The API is compliant with the standard SDMX RESTful web services specification.

The Community Edition REST API supports the following key functions:

• Query for structures - retrieve selected SDMX structures
• Submit metadata content - add new structures to the metadata registry or update existing ones such as adding codes to a code list
• Delete metadata content - delete selected structures from the metadata registry
• Query for schemas - retrieve XML schemas for selected structures
• Data conversion - conversion of data between SDMX formats and versions
• Data validation - validate the structure of data for compliance with the data model

Data Essentials and the Enterprise Edition provides additional functions covering loading data, registering data sources and querying for data including:

• Query for data - retrieve data for a specified selection of series from a dataset
• Submit data content - load data into local Fusion Registry managed data stores, including the in-memory database
• Delete data content - delete selected datasets, series and observations
• Rollback data change - rollback data submissions
• Data registration - registration of external data sources
• Data reporting forms - generate Excel forms for reporting data
• Freetext search - search the metadata and data content

The Enterprise Edition also supports:

• Reference metadata - query for and submit reference metadata
• Audit - query audit logs
• Fusion Edge Server - generate data and metadata packages for publication to Fusion Edge Servers
• Content Security - query for and manage Content Security rules

Operating System - Windows or Linux. Other platforms including Apple Mac, HP-UX and IBM AIX should also work provided they have a suitable Java Runtime Environment (JRE) or Java Development Kit (JDK), and Java Web Application Server.

Java Runtime Environment - Java 8 and Java 10 are supported.

Java Web Application Server - Apache Tomcat 8.0, 8.5 or 9.0 are recommended. Jetty is also tested and proven. Other application servers like IBM WebSphere Application Server should also work.

Processor - A minimum of 2 cores for the Community Edition, and 4 cores for the Enterprise Edition.

Memory- 4GB is sufficient for the Community Edition. A minimum of 8GB is recommended for the Enterprise Edition Core. More memory will be required if heavy in-memory database use is planned. The Fusion Edge Server and Fusion Reporting Node both utilise the in-memory database so a minimum of 8GB should be provided for those deployments.

Web Server - A web server is recommended working in reverse-proxy mode for all production systems. Apache Web Server 2.4 is recommended although cloud deployment platforms such as Amazon Web Services and Microsoft Azure generally provide a reverse proxy service meaning that Apache is not required in those circumstances.

The Community Edition and Data Essentials use the same core SDMX engine. To upgrade, simply stop the Java web application server, deploy the Data Essentials software distribution and restart the application server.