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 the transfers using a single tool – Adoki.

Today, companies have many times more data at their disposal than they did a few years ago. And they are also using more applications, systems, data stores – all in a variety of on-premise, cloud and hybrid environments. It’s clear that in this complex and often highly sophisticated IT ecosystem, organizations have increased the requirements for data transfers. It has become prohibitively time-consuming and resource-intensive to prepare data transfers manually, and demand for automated setup, management and monitoring is increasingly acute.

At Adastra, we’ve had decades of experience with data transfers, and we’ve built numerous data warehouses, analytics and data platforms onto which we’ve had to move data.

We realized it couldn’t be done without automation. That’s why we developed Adoki

Every day, we face a situation where a large corporation or government body needs data for a technical or business department but does not have those data readily available. This is related to the large number of different systems and applications, including mobile apps, that generate data in various forms. To be fully utilized, those data need to be properly adapted, i.e., transformed and delivered to places where the specialist departments can actually use them. In today’s IT ecosystems, transformations are enormously complex and intricate; data transfers, meanwhile, must be seamless, secure and, above all, reliable.

This is ensured by “extract, transform, load” (ETL) tools. Their task is to ease the burden on primary systems, to pick up data regardless of where and what kind they are, transform them into the required format, and load them to the target location.

The main benefit offered by ETL tools is conserving human resources in IT departments

ETL tools must be able to do the following:

  • connect to the necessary data sources
  • transfer data quickly and efficiently
  • perform all necessary data modifications
  • make data transfer configuration as simple as possible
  • provide long-term maintenance for data transfers

Current ETL tools can be divided into two categories:

support a narrow set of data sources but a wide variety of data modifications
support a large set of data sources but a limited range of data modifications

Adoki numbers among the generalists

Adoki connects and transforms data across a broad range of systems. At the same time, it allows the user to translate data types automatically and change data forms freely. Data transfers are also created automatically. It’s been a long time since customers were satisfied with transferring just a few hundred data objects that could still be “clicked”, but Adoki can do that too. You’ll appreciate Adoki most during initial data acquisition or when you need exact copies of the data in multiple target locations.

Just like competing ETL tools, Adoki:

  • transfers data between files, databases, streaming systems and clouds
  • supports basic data transformations, column and row filters, parsing for nested structures (json, xml, avro, etc.), and similar object-level operations
  • supports full and incremental transfers
  • allows custom data-processing modules to be added
  • enjoys extensive system support – see the image

All this and more – or what else Adoki can do in comparison with other ETL tools

Adoki is the most suitable tool for implementing recurring transfers of large volumes of data, which often run simultaneously or whose execution is time-sensitive due to the load on the IT infrastructure. You can take advantage of all Adoki’s features if you’re looking for a tool that

  • can take care of data transfers long term without any need for user intervention
  • supports many different connectors; you can even add your own connectors
  • is based on the automatic synchronization of transfer metadata and the subsequent deployment of data structures, data migration and long-term maintenance
  • can take care of the transferred data – operations such as compaction, retention, statistics, automatically modifying data schemas
  • significantly eases users’ work – the user does not have to add anything, as Adoki can look up all the necessary inputs and, through its REST API, generate and service all the data transfers automatically without any user input
  • can advise how data should be transferred by automatically recommending data type conversions between systems
  • transfers data regularly, every second, minute, hour, day or on demand
  • monitors the load on the systems to which it is connected, scaling the resources being used and selecting the objects to be transferred according to the resources available
  • can run anywhere – Adoki can be run on existing hardware or in a cloud environment; unlike other ETL tools, it does not require any specific hardware
  • serves not only IT teams but also data scientists and business users who create data layers (e.g., reporting layers)

Author: Marcel Vrobel, Adoki CTO, Adastra