Become a data-driven company where tens of thousands of data transfers per day are handled by a single person – reliably, safely, automatically thanks to Adoki.
Free demo versionAdastra has been a Select Partner of Cloudera since 2014 and has also achieved technology certification for the Adoki solution.
Replicate, synchronize, distribute, consolidate, migrate, snapshot and ingest data from any systems or databases.
Automatically generate target schemas based on source metadata.
Scale up to hundreds of sources and targets.
Safeguard the consistency and integrity of all data structures.
Minimize impact, i.e., it does not overload source or target systems.
It can be set up quickly and easily using an intuitive graphical interface (GUI), without any manual programming.
Makes it easy to configure data transformations, even during data transfers.
Transfer data in legacy enterprise and hybrid environments – in real-time or batch mode.
Centralize data transfer monitoring and management. Thanks to detailed logs, all transfers can be audited.
Customizable modular solution to fit organization processes.
Same data on-premise and on cloud? With Adoki, the automatic data replication tool, it’s a simple matter.
Adoki enables companies to efficiently replicate data between systems, i.e. generate and scale data transfers. It centrally manages and monitors data transfers to and from any data platform (on-premise and cloud) based on metadata.
It uses native solutions and connectors to link to any data repository. It creates and automatically checks data schemes and ensures that data is consistent at all times.
It transfers data quickly, efficiently and securely. Provides statistics to automatically optimize data transfers.
of data transmissions managed by a single person
Adoki easily replicates tens of TB of data per day
To different applications, systems, databases, in the formats you require, to on-premise and cloud environments?
And how do you get it there securely, in consistent structures, at the time you want it, and have full control over its flow?
Meet Adoki!
Businesses need to move data from one platform to another (or other systems that are on-premise, hybrid or cloud-based) and they need to keep data in sync at all times.
The goal is to keep the data consistent (i.e., have an updated structure if it changes in the source systems) and also to be able to delete some data after a set period of time.
Komplex approach
Metadata storage
Evaluating schemes
Companies need to perform data analysis and Data Science tasks over data from multiple systems.
Data needs to be transformed and anonymized, available as soon as possible and GDPR compliant. The results are sent back to the source systems.
Complex scenarios
Easy transformations
Schedule
REST API
Companies need to transfer data from on-premise systems to the Cloud, but often don’t have the necessary knowledge or infrastructure.
Data needs to be replicated to the Cloud at minimal cost.
Custom mapping type
Incremental upload
Simple transformations
Resource management
Companies need to optimize system utilization during replication to save system resources and monitor ongoing activities.
Typically, they use traditional ETL tools, but the number of concurrent data transfers is increasing and systems have capacity issues with the number of jobs running.
Resource management and monitoring
Runs directly on the Big Data platform
Traffic statistics
Metadata repository
Adoki automatically replicates any files, tables and databases to the data lake. It uses predefined scenarios that take into account the requirements of the source and target.
The most commonly used scenarios include the mirror scenario, which replicates data from the source systems to the stage layer, where the data is unified and checked. It is then published to the mirror layer, which provides a copy of the data for quick reading and use.
The mirror stage also allows the creation of an archive layer that acts as an economical backup of the data for regulatory and technical purposes.
Adoki can transform, anonymize and filter data from on-premise systems before replicating it to various cloud technologies. It can be deployed both on-premise and in the cloud.
Adoki knows how much the connected systems load the infrastructure and what performance each transfer needs. This allows it to manage and scale replications (up and down).
Developers and operators work with Adoki through an intuitive graphical user interface.
Adoki offers a REST interface for systems and automated frameworks.
Adoki provides dashboards in Elastic/Kibana, an open-source tool for visualizing processed logs.
Users access Adoki through a web interface that allows them to:
Set up what to transfer and how, plan when and how often the transfer should occur, etc.
Set limits on individual systems, for example, on the number of connections, memory size, etc.
Turn them on or off, change the priority of a transfer, track its progress, set up notifications about the progress, etc.
Browse the transfer history, track statistics, monitor platform load, etc.
In 2018-19, Adastra built an on-premise Data Analytics Platform (DAP) at ŠKODA AUTO. Its purpose? To visualize data and use advanced analytics and artificial intelligence to perform sophisticated tasks with large volumes of data.
A large automotive company works efficiently with (IoT) sensor data from manufacturing. We have lightened the system load and introduced data retention in the...
At the bank, we have created a Big Data platform that provides business users with streamed and batch data from various banking applications. To...
By integrating data directly from the JIRA source system, we are able to prepare a detailed overview of the status of multiple projects, including...
One large Czech bank handles tens of thousands of data transfers every day. How many people does that take? Just one, who manages all...
Companies who base their business on data generate more revenue than those who rely on intuition or other approaches in their decision-making. Don’t risk...
It is increasingly necessary for companies to have the same data in various systems. In this context, data virtualization has become rather a hot...