Hydrograph Overview

Hydrograph is the next-gen GUI-based data integration tool designed by Bitwise to enable greater efficiency from ground up during your ETL development. Hydrograph addresses the need for better and more agile ETL functionality on Hadoop in enterprises with big data workloads without having to write MapReduce/Spark code and is built on cloud native architecture for efficient data integration.

Built by practitioners who understand the pains of offloading ETL on Hadoop/Big Data, Hydrograph is engineered to accelerate ETL development in the big data and is available in both On-Premise and Cloud platforms (AWS, GCP and Azure).

Benefits of our Data Integration Tool

Hydrograph helps enterprises bridge gaps between the ETL tools that developers are familiar with, and Hadoop/Spark for meeting critical reporting and analytical requirements.

bitwise- hydrograph

It provides the following key benefits:

  • Easy-to-use: The Hydrograph development environment is convenient and easy-to-use as it requires minimal retraining for ETL developers.
  • High Processing Power: Hydrograph enables you to harness the processing power of Big Data, resulting in up to 33% faster execution time in Spark compared to legacy ETL tools.
  • Offloading: Hydrograph provides the ability to offload legacy Teradata, Netezza or Big Data Appliance ETLs to modern Big Data ecosystem.
  • Scalability: Hydrograph empowers you to create scalable applications that can meet today’s technology requirements while seamlessly managing future growth.
  • Use Case Applications: In an agile environment, Hydrograph gives you the ability to deliver new use case applications.
Bitwise - Hydrograph process framework

Features of Hydrograph

Input / Output Components

  • File I/O: Delimited, Fixed Width, Mixed Scheme, XML, Avro, Parquet
  • Hive I/O: Text, Parquet, RC, ORC, Avro, Sequence
  • RDBMS: Oracle, Teradata, MySQL, Redshift, MS SQL Server, Generic JDBC I/O, IBM DB2 I/O, Netezza I/O
  • Semi-Structured Files: EBCDIC, JSON, Regex Input, Excel files
  • Kafka I/O
  • Cloud Data Warehouse: Snowflake I/O, BigQuery, AWS Glue, Cloud SQL, PubSub
  • NoSQL: MongoDB I/O, Hbase I/O, Cassandra I/O

Execution Engine

  • Spark Batch, MapReduce
  • Spark Streaming, AWS Glue


  • Subjobs and parameterization for creating reusable jobs
  • Execution Tracking visuals
  • Generic Jobs – By externalization of transform logic
  • Problems View
  • Grid view for displaying logs
  • Unit Testing Framework
  • Schema Import Wizard

Transformation Capabilities

  • Date, String, Numeric Functions for transformations
  • Standard ETL transformation components
  • Support for encryption/decryption, hashing, geospatial functions
  • REST and SOAP web service component
  • Conditional schema while reading files
  • Vector Functions
  • CDC (Change Data Capture) component

Over the years, Bitwise has partnered with businesses from diverse industries to successfully enable a strategic and efficient ETL development process with Hydrograph through a more modern data processing environment.

Accelerate Your Data

Contact Sales

Other Offerings

Discover Services and Solutions that can make your data do more