Big Data Integration

Big Data Integration

Data is the new competitive battleground making it more important than ever to get an edge up on your competition with a fast, multi-point and modern approach to big data integration. With SnapLogic’s easy to use big data integration platform as a service (iPaaS), you’ll be able to quickly ingest, prepare and deliver data, whether the source is on premises, in the cloud or in a hybrid cloud environment.

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Thanks to Hadoop, Spark and other big data processing engines, enterprise IT organizations and developers are now able to process and store massive volumes and varieties of data, which is then ending up in big data lakes, hubs and repositories. Feeding, reading and analyzing large amounts of unstructured, complex or social data can prove challenging for most integration vendors. Not so for SnapLogic. SnapLogic’s distributed, web-oriented architecture is a natural fit for consuming large data sets residing on premises, in the cloud, or both – giving maximum visibility to your big data analytics.

SnapLogic’s platform-agnostic approach decouples data processing specification from execution. As data volume or latency requirements change, the same pipeline can be used just by changing the target data platform. Whether it’s Hadoop, ETL, Spark or other big data frameworks, SnapLogic allows customers to adapt to new data requirements without locking them into a specific framework.


Spark Script Snap Pipeline
The Spark Snap enables customers to create Spark-based data pipelines without coding. These high-performance pipelines are ideally suited for memory-intensive, iterative processes. With this addition, customers can choose to use either MapReduce or Spark for data processing, depending upon factors such as data size, latency requirements and connectivity.

The Sparkplex is a data processing platform that features a collection of processing nodes or containers that can take data pipelines, convert them to the Spark framework, and then execute them on a cluster. The combination of the Spark Snap and Sparkplex gives customers the speed benefits of Spark data analytics without the time and effort involved in creating and maintaining hand-coded integration between data sources and a Spark cluster.

Big Data Analytics

As you invest in Hadoop distributions like Cloudera, Hortonworks and MapR, it becomes increasingly difficult to find and afford the technical resources to effectively perform complex, time-consuming tasks such as moving data into and out of the Hadoop system. This is where SnapLogic can make your data scientists more productive and effective, by offloading much of this work. The SnapLogic Enterprise Integration Platform has been certified for Cloudera CDH5 and Hortonworks HDP2.3.

SnapReduce enables SnapLogic to run natively on Hadoop as a YARN-managed resource that elastically scales out to power big data analytics. With SnapReduce, SnapLogic becomes a YARN application allowing Hadoop users to take advantage of an HTML5-based drag-and-drop user interface, breadth of connectivity (called Snaps) and modern architecture.

Big Data Analytics

SnapLogic and Big Data

With powerful application and big data integration in a single platform, SnapLogic connects enterprise applications and data stores with minimal coding, helping you get from big interactions to big insights more quickly and easily than any other integration solution:

  • Comprehensive connectivity to Spark and Hadoop with pre-built Snaps for Spark, Cassandra, HBase, HDFS and more
  • Hadoop extract, transform and load and ELT that has been certified for Cloudera and Hortonworks
  • Pre-built connectivity to 300+ data sources that can easily be loaded into Hadoop, Spark or Microsoft Azure HDInsights
  • Big Data on-demand for both expert and self-service users, making data scientists more productive by letting them focus on business insights, not data integration

Big Data Analytics

The SnapLogic Snaplex can run as a native YARN application in your Hadoop cluster.

"Your next-gen data management strategy must be informed by the current and future requirements of your entire business or it will be doomed to fail. But, it also must be pragmatic for you to implement it successfully."
Mike Gualtieri and Nasry Angel, Forrester Research


  • SnapLogic for Big Data Integration Datasheet
  • SnapLogic Brings Big Data Integration to iPaaS Press Release
  • SnapLogic Big Data Integration Processing Platforms Whitepaper
  • SnapReduce 2.0: Big Data Integration for Hadoop Demo
  • Hadoop for Humans: Introduce SnapReduce 2.0 Webinar
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