Fast Data Ingest/ETL

While Data Ingest is a component of many data pipelines, it also stands alone as a well-bounded computing challenge that can greatly benefit from an accelerated Big Data Ingest approach. Fast Data Ingest is especially needed for high-volume ETL for Data Lakes, as well as Hadoop powered EDW, IoT data capture, and a host of other similar applications.

Hyper-acceleration without changing your code. Read the Bigstream Hyper-acceleration whitepaper to understand how.

The need for acceleration of data ingestion tools and ELT processes comes from the fact that moving data is often one of the most expensive and important operations in a Big Data pipeline. Data engineering and performance engineering teams know that the best option is to leave data in place, but for some operations there is no choice.

Bigstream focuses on these key parts of the Ingest pipeline:

  • High-speed data connectors to Amazon S3, Kafka and Hadoop File System (HDFS)
  • Hyper-accelerated compression and decompression of GZIP, snappy, DEFLATE and LZO formats
  • Hyper-accelerated parsing of JSON, Avro, CSV and Parquet documents/data

Bigstream Hyper-acceleration provides a performance boost at several critical stages of Big Data Ingest:

Bigstream benchmark testing shows 4X+ Hyper-acceleration CSV parsing with work underway on similar speedups for JSON, Parquet, and more.

Read the Bigstream Benchmark Report to see how Bigstream Hyper-acceleration will transform your Big Data Ingest operations.