Adoki – Data Integration Platform

Are you building a new data platform in the cloud, on-premise, or in a hybrid environment, and need to transfer data to it either once or on a recurring basis?

Integrate with Adoki. It will handle all data transfers to the new platform and back – automatically.

Try a free demo

Acquire, replicate, and migrate your data automatically


Data still available


Easy data integration


Support for a wide range of platforms


Easy deployment


All in one place

Connect technology platforms and systems

Adoki does the work for you

Transfer and migrate large numbers of tables

  • Adoki scans your data source.
  • You choose a template for how you want to transfer the tables.
  • Adoki itself suggests the best way to transfer and ensures the transfer – whether it’s a one-time or regular process.
  • If the source changes, just re-scan it, and Adoki will automatically apply all changes.

Automatically process data from files including their structures to another system

  • Adoki scans files in various formats (xml, json, avro, parquet, csv, etc.).
  • You choose a template for where you want to transfer the files.
  • Adoki itself suggests the best way to do it and ensures the transfer.
  • Adoki automatically searches for new files to process at the inputs.

Stream data easily

  • Adoki can scan schema registries (e.g., confluent for Apache Kafka) and download the necessary metadata from it.
  • You select what you want to transfer and how often.
  • Adoki ensures that data flows either in batches or in real-time.

Automatically synchronise structure changes

  • Adoki automatically detects changes in tables and files.
  • It can apply these changes during transfers.
  • Adoki ensures that the data is properly synchronized and consistent.

One person handles 10,000 data transmissions

Adoki efficiently transfers data to and from any data platform or system (data warehouse/database, cloud, Hadoop platforms, or streaming applications), both on a one-time and recurring basis.

It takes into account the IT infrastructure load of the organization and, if necessary, can shift data transfer or replication to an optimal time.

It centrally manages and monitors data transfers. As a result, you can manage with a smaller team of specialists than before.

Find out how Adoki will make your work easier and your data transfers more efficient


One man instead of a team of specialists

One person manages 10,000 data transmissions instead of the team of experts previously needed.


Intuitive graphical interface

Centralizes the monitoring and management of data traffic into a user-friendly graphical interface.


One tool instead of many

It has connectors to all major technologies and has an open interface for creating additional/required connectors.

Make the most of the Adoki...


  • Simple user interface to generate data transfers
  • You don’t need to be an IT specialist

Audit trail

  • Allows you to see in detail where the data is flowing and how it flows through all the links of the set transmission
  • Immediately alerts you to a possible error and when and where it happened

Data Governance

  • Ensures data transfer without delay
  • Can translate complex data structures
  • Performs basic operations to improve data quality

Team efficiency

  • Saves time and team capacity
  • Simply set the path, the data is transferred automatically
  • A few clicks and you know exactly where the problem is

...and simplify your work with the tool's unique features

Easy integration

With its modular architecture, it can be easily integrated into an organisation’s IT environment without the need to purchase additional HW or SW.

Prioritization of data traffic

It can take advantage of dead spots and times for data transfers, runs data transfers and replications on a schedule, and can split large transfers into smaller ones.

Optimising computing power

Automatically optimizes data transfers to maximize computing power and not limit platform traffic.

Notices of incomplete transmissions

Sends alerts about pending or incomplete data transfers, integrations, or errors.

10x WHY get Adoki

From a business perspective:

  1. You need to share data from systems of various departments within the organization.
  2. You are building a data platform and need to ensure data delivery to it.
  3. You have dozens to hundreds of systems and need to connect them.
  4. You need to have data simultaneously in multiple locations, both on-premise and in the cloud.
  5. You need to add more data to existing/current data.
  6. You are looking for a simple and reliable solution for moving data.
  7. You need to systematically archive and back up data.
  8. You repeatedly face issues with data transfers: they don’t transfer, they break, they duplicate.
  9. You need to provide anonymized data to analysts due to GDPR.
  10. You are looking for a tool that ensures input data does not contain errors.

From an IT perspective:

  1. You need to free up developer capacity for creating/solving business cases.
  2. You want automation; you don’t want to manually create new/additional data transfers.
  3. You want simple maintenance and monitoring.
  4. You need to monitor changing data structures.
  5. You need to speed up the setup of new and modifications of existing data transfers.
  6. You want to limit the load on IT infrastructure during peak operations.
  7. You want to manage, audit, and control data transfers from a single location.
  8. You need to automatically rectify deficiencies in data sources.
  9. You want a metadata-driven tool that further provides to the organization.
  10. You are looking for a tool with the option of additional functionalities and modules.

Connect to any data platform you want

Leverage the versatility of Adoki and connect with it to any data platforms, including streaming ones, databases, and files. The most important ones can be found in the image. If you're interested in others, please contact us.


Adoki use scenarios


When you need to transfer data from on-premise systems to the cloud, but often lack the necessary knowledge or infrastructure. Moreover, data must be replicated to the cloud at minimal cost.


Custom Mapping Type

  • Cloud object schemas are automatically generated based on the schemas of objects in the on-premise environment.
    For selected cases, schema generation can be adjusted.

Incremental Loading

  • Only the desired subsets of data are replicated, and their increments are processed automatically.

Simple Transformations

  • You only work with a subset of the data, and transformations/anonymizations are done before they are stored in the cloud.
    Data storage is efficient.

Resource Management

  • It monitors how many cloud resources are actually being used.


The ideal solution when you need to transfer data from one platform to another, or to other systems that are on-premise, hybrid, or cloud-based, and need to keep data consistently synchronized in them.

The goal is to ensure the data is consistent (i.e., it has an updated structure if changes occur in the source systems) and also to be able to delete certain data after a specified period.


Comprehensive Scenarios

  • Adoki defines scenarios and applies them to a large number of objects.
    These scenarios allow you to generate metadata, convert data types, predefine columns and operations, and load multiple tables at once.
  • Data can be grouped into tasks, ensuring they are transferred simultaneously and maintaining their consistency.

Metadata Storage

  • All scenarios are stored and versioned in the metadata repository.

Schema Evaluation

  • Structures generated based on source metadata can be automatically deployed to target platforms and adjusted in case of changes.


Optimize system utilization during replications to simultaneously conserve system resources and maintain visibility into ongoing activities. Avoid typical capacity issues associated with the number of tasks initiated when involving traditional ETL tools.


Resource Management and Monitoring

  • Resource capacities and time locks are defined for each system.
  • Resource capacities are taken into account and workload is optimized.

Runs Directly on the Big Data Platform

  • Adoki can be deployed onto existing platforms as a module, thus reducing hardware requirements.

Transfer Statistics

  • Adoki provides detailed statistics on resource utilization, which can be used to optimize workload.

Metadata Storage

  • Metadata from Adoki can be exported via the REST API interface, allowing it to be utilized by other tools.


Execute data analyses and Data Science tasks using data from multiple systems, ensuring that the data is correctly transformed, anonymized, made available as soon as possible, and compliant with GDPR. Also, receive the results back into the source systems.


Comprehensive Approach

  • The request process is straightforward.
  • Ready for end-users to process – priority transfers.
  • Every data transfer is assigned a priority; critical tasks must be processed as soon as possible.

Easy Transformations

  • Data can be transformed and anonymized within the replication process.


  • Individual tasks can be scheduled.


  • Once the data is ready for transfer, users receive a notification.

Try a free demo!

Experience for yourself how a single person can set up and manage hundreds of data transfers with Adoki.

Try out how working with Adoki would feel, discover its full capabilities, and see how simple data transfers become with it.

No specific software technologies are required to run the demo. The demo operates without any installation in a standard web browser. We will send you login credentials to our cloud environment, and you can start exploring.

Try a free demo

Our case studies

ŠKODA AUTO: data transfers on analytics platform are comprehensively managed and monitored by Adastra’s Adoki

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.

use the solution implemented by Adastra

is the total data storage capacity

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Integrating 8 IoT databases and 1 metadatabase to reduce load and save space in the source system

A large automotive company works efficiently with (IoT) sensor data from manufacturing. We have lightened the system load and introduced data retention in the...

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Banking – data in one place, we transfer 4 TB of data per day

At the bank, we have created a Big Data platform that provides business users with streamed and batch data from various banking applications. To...

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Integrating JIRA data to identify risk

By integrating data directly from the JIRA source system, we are able to prepare a detailed overview of the status of multiple projects, including...

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Get inspired on our blog

Adoki: automates ETL data transfers and breaks down corporate data silos

One large Czech bank handles tens of thousands of data transfers every day. How many people does that take? Just one, who manages all...

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8 tips for building mature Big Data platforms

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...

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When use data virtualization and when replication? Three key criteria based on out best practise to consider when making a decision

It is increasingly necessary for companies to have the same data in various systems. In this context, data virtualization has become rather a hot...

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