Neoflex Datagram

Neoflex Datagram allows you to create highly loaded analytical business applications for data processing using Big Data technologies.

2022: Neoflex Datagram - Russian replacement for IBM Infosphere, Oracle Data Integrator and other Western ETL platforms

Today, a number of Russian ETL platforms are presented on the market, which can reliably replace the usual solutions. Among them is the Neoflex Datagram platform from a company with many years of experience in designing and implementing data warehouses. Read more here.

2020: Inclusion in the unified register of Russian programs

Neoflex Datagram is included in the unified register of Russian programs for electronic computers and databases. This became known on June 29, 2020.

Customers both in and Russia abroad have already appreciated the use of Neoflex Datagram to create analytical applications using the technology stack. Big Data Thanks to the Model Driven Architecture approach behind Neoflex Datagram, developers can design data processes visual in an editor, and executable Scala code will be generated automatically. Thus, ETL and - can be involved in creating Big Data solutions, SQLprogrammers which significantly speeds up the development process and helps solve the problem of a shortage of Big Data specialists.

Neoflex Datagram uses the Apache Spark library and supports both batch and streaming processing mode. The core of the platform is a metadata server containing information about data sources and receivers, runtime environments, transformations, job sequence, etc. Neoflex Datagram supports a full development cycle, including compiling and generating the application, deploying it to the runtime, and scheduling execution.

Among the main capabilities of Neoflex Datagram: the creation of parallel and serial data conversion schemes; support for shell scripts and java programs; You can create transformation sequence control schemes using nested Workflow objects. Scheduled Workflow execution by time or file system events.

Neoflex Datagram reduces the time to develop business applications for online monitoring and detection of anomalies in streaming mode, high-load applications for data processing and analysis, systems for automating mandatory reporting in large financial organizations.