StreamAnalytix Integrations and Operators

StreamAnalytix integrates various key big data technologies, including support for multiple big data compute engines, a powerful array of pre-built connectors and operators to various systems, and functional extensibility for future readiness. StreamAnalytix integrates smoothly into the Enterprise technology eco-system without imposing any lock-ins or creating new data silos.

Cloud Platform Integration

Deploy on both on-premise and cloud infrastructure

Amazon Web Services

Microsoft Azure

Google Cloud Platform

Databricks

Cloud Technologies

Amazon RDS

Amazon EC2

Amazon EMR

Amazon S3

Amazon Kinesis

Amazon Red Shift

AWS-IOT

Amazon Sagemaker

Azure Blog Storage

Azure VM

Azure HDI

Azure Event Hub

SQL DW

Cognitive Services

Google VM

Hadoop Integration

Supports all key Hadoop distributions

MapR

Cloudera

Hortonworks

AWS EMR

Microsoft HDInsight

DataStax Enterprise

Event Processing and Analytics Engines

Get a consistent user-experience across multiple big data compute engines

Apache Spark

Apache Spark Streaming

Apache Spark Structured Streaming

Apache Storm

Apache Flink

Oozie

TensorFlow

Data Ingestion and Data Sinks

Connect with any data source and data storage system for both streaming and batch use cases on-demand

Message Queues

Apache Kafka

RabbitMQ

MapR Streams

MQTT

OpenJMS

TIBCO JMS

ActiveMQ

Distributed File Systems and supported file type

HDFS

Hive

SFTP

Local File System (Via Agent)

Microsoft Excel

Apache Parquet

Advanced-HDFS

Binary

No SQL

Hbase

MongoDB

Cassandra

Couchbase

JDBC

Oracle

Hive

Postgres

Redshift

SQL Server

Indexing Stores

Elasticsearch

Solr

Third Party Platforms

Marketo

Salesforce

Attunity

Mailchimp

Other

TwitterStream

HTTP

ClickStream

RSS Feed

Sockets

Web Sockets

Data Generator

Custom Channel

Google Analytics

Facebook

YouTube Analytics

Magento

Data Preparation and Processing

Perform in-memory data transformation to prepare for advanced analytics and machine learning jobs

Persistence and Caching

Persist and re-purpose data

Persist

Predictive Analytics, Machine Learning, and Deep Learning

Use advanced analytics and machine learning operators on both real-time and batch data, at scale

SparkMLlib

SparkML

H2O

TensorFlow

PMML

Spark ML

Linear Regression

Logistic Regression

Isotonic Regression

Naïve Bayes

Tree Model

Decision Tree

k-Means

Random Forest

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