Big Data


When to consider the Big Data solution?

✓  The company's infrastructure contains large data sources or wants to integrate these sources into its own processes (usually data meeting "5V")
✓  The company processes a large amount of data streams and unstructured datasets
✓  The company is not interested in building an IT department based on inflexible hardcoding operations demanding rapid change according to new requirements
✓  Analytical operations on large data sources are complicated and require long-term employment of data specialists able to create optimized algorithms for Big Data systems
✓  The company is looking for an integration tool capable of working seamlessly with the classic integration environment and at the same time in the environment of the most used Hadoop distribution systems and associated platforms

How will the Big Data solution help your business?

With the Big Data solution, the company is able to easily and without complications manage the transition to a new era of processing unstructured data in large volumes. Data Integration, Data Quality and Electronic Services operations can be easily transformed into processes operating in a Hadoop environment through native code transformation with support for the most famous Big Data distributions such as Cloudera, Hortonworks, MapR and others. Ready-made components for working in HDFS environment help in creating and managing your own DataLake, as well as with aggregation of raw data into processable outputs using Hive, Impala or Kudu support.

All this with the support of an expanding base of components with a predefined range of algorithms for Machine Learning and the possibility of extension to neural networks.

If you've already started building a Data Lake or streaming integrations, Big Data is ready to work in platform environments such as Azure, Amazon, Google, Snowflake, etc., to ensure the management of your resources under one integration platform.

The background of the strong Talend platform operating at the international level ensures the possibility of adapting to the latest technologies and procedures before they are recognized at the local level (it offers a market direction compass).

Main advantages

+  Short "learning curve" for working with Big Data integrations (time saved)
+  Automatic code conversion of classic integration processes into native Big Data processes executable in clusters
+  In-memory processing support under Apache Spark
+  No knowledge of hardcoding operations with Pig, Scala, R, HiveQL, etc.
+  Custom management of all data sources
+  Elimination of dependence on third-party suppliers and partial systems
+  Fast creation of new data sources and integrations
+  One-stop-shop administration “under your own roof”
+  Support for a strong open community of developers
+  Easy integration cost planning
+  Flexible and clear licensing policy without additional fees for data volumes and numbers of integrations

A comprehensive Data Fabric solution consists of the following functional areas:


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In addition to the often used on-premise type of installation, Talend also offers a hybrid or cloud installation, which you can read more about here.