Integrated DataOps development and operations platform for building, deploying and running cloud-based data warehouses. Data modeling, ELT & orchestration capabilities combined in the same software.Go to features
"Truly exceptional concept! I'm also happy to say that we've been running our own data platform on it for two years now and it's working like a charm."
Agile Data Engine supports your multi-domain data and multi-site teams with multi-tiered architecture and multi-phased continuous deployment to isolated Development, Test and Production environments.
"Agile Data Engine allows us to focus on what is important – producing value. We do not have to think about the release process when everything works automatically."
Agile Data Engine has an automated and configurable cloud infrastructure set-up enabling Development/Test/Production environments’ isolation and fast start-up of the project.
Agile Data Engine is built with multi-cloud and multi-DBMS support for easy transition from a cloud/DBMS service to another. It is also about being future-proof enabling support to-be-developed to new market leading cloud/DBMS services to come. Currently it supports AWS & Azure in cloud and Snowflake, Amazon Redshift, Azure Synapse SQL, Azure SQL Database & Google BigQuery in DBMS services.
Agile Data Engine has a unique entity-driven approach for implementing data models and data transformations together to enable modularity in data warehouse development. All data warehouse modeling methodologies are supported.
Data Vault 2.0 automation for generating data vault entity loads and accelerating data modeling.
Graphical data lineage view with data warehouse entities and loads, with metadata based search. Lineage helps data professionals in managing the whole data platform solution content and helps in troubleshooting and understanding the audit trail of the data loads.
Continuous deployment framework manages the deployment pipeline of data warehouse solution packages from Design to Development/Test/Production runtime environments.
Data model deployment is a fully automated process and the automatic change detection of schema happens in runtime based on the metadata. The framework supports multiple DBMS services (currently Snowflake, Amazon Redshift, Azure Synapse SQL, Azure SQL Database and Google BigQuery). No need for schema compare tools and incremental change scripts for data model and grants/revokes.
Data workflows (as directed acyclic graphs) are dynamically generated based on entities’ load dependencies and scheduling information in the metadata repository.
There are a multitude of ways to ingest and integrate source data into cloud data platforms and Agile Data Engine enables the use of these based on source data and workload requirements. Regardless of style, ingestion to database platform is harmonized with Agile Data Engine DW input interface.
Agile Data Engine provides functionality to crawl both metadata and data from JDBC supported database sources.
Agile Data Engine utilises an ELT approach instead of ETL, which means that data processing/compute capacity is based on the cloud database platform and therefore the processing capacity can be scaled easily, when requirements change. Processing of data can also be done with other cloud-based processing technologies (e.g. Spark) and integrated into Agile Data Engine’s orchestration engine.
Integrated and customizable data smoke tests as part of the data workflows, that monitor data quality continuously and can be used to control the execution of workflows or to flag warnings.
Agile Data Engine’s Dagger component utilises Apache Airflow open source software as the data orchestration platform. Airflow is integrated together with Agile Data Engine software, so Airflow DAG codes are dynamically generated based on the metadata.
Faster time-to-delivery & experiments
Lower total cost of ownership
Data capability that adapts and scales
"We can develop at an entirely different rate. In practice, the improvement is in multiple percentages. We previously saw development cycle turnarounds in weeks – now they happen in days.”
Does your data warehousing team underperform and struggle to satisfy the increasingly challenging data requirements coming from business? Do you want to know how to achieve 4X value from your cloud data platform?
Do you have a need to migrate your existing data warehouse to cloud and need to do it as fast as possible, but without compromising the architecture?