Get started with Hydrograph ETL for Big Data
Hydrograph
ETL for Big Data
Hydrograph is a GUI-based ETL tool built to efficiently process big data workloads on premise or on the cloud without needing to write MapReduce/Spark code.
Efficiently Process Big Data with GUI-based ETL Tool
Hydrograph enables enterprises to leverage their developers’ existing skillsets by providing an effective way to build ETLs on Hadoop using a drag-and-drop user interface harnessing the power of Spark and other big data processing engines. Hydrograph is available for both On-Premise and Cloud platforms (AWS, GCP and Azure).
Modern ETL tool to fit your current and future technology strategy
Key Benefits:
Easy-to-Use
Easy-to-use development environment that requires minimal retraining for ETL developers.
Faster Execution
Harness the processing power of Big Data (up to 33% faster execution time in Spark compared to legacy ETL tools).
Offload Legacy
Ability to offload legacy Teradata, Netezza or Big Data Appliance ETLs to modern Big Data ecosystem.
Deliver New Use Case
Ability to deliver new use case applications in an agile environment.
Create Scalable Applications
Ability to create scalable applications that meet today’s technology requirements but flexible for future growth.
Features
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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
Execution
- Spark Batch, MapReduce
- Spark Streaming, AWS Glue
Usability
Usability
- 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
Ready for a modern big data ETL tool?
Helpful Resources
Bitwise provides comprehensive solutions for all your data projects
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