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.

Hadoop Integration

Supports all key Hadoop distributions

MapR

Cloudera

Hortonworks

AWS EMR

Microsoft HDInsight

DataStax Enterprise

Cloud Platform Integration

Deploy on both on-premise and cloud infrastructure

Amazon Web Services

Microsoft Azure

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)

Advanced-HDFS

Microsoft Excel

Apache Parquet

Binary

Cloud Sources

Amazon S3

Redshift

Amazon Kinesis

AWS-IOT

AWS Dynamo DB

Amazon SQS

Azure Event Hub

Azure Blob Storage

No SQL

Hbase

MongoDB

Cassandra

Couchbase

JDBC

Oracle

Hive

Postgres

Redshift

SQL Server

Indexing Stores

Elasticsearch

Solr

Third Party Platforms

Marketo

Salesforce

Attunity

Other

TwitterStream

HTTP

ClickStream

RSS Feed

Sockets

Web Sockets

Data Generator

Custom Channel

Data Preparation and Processing

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

Data Transformation

Masking

Encoder

Decoder

FlatMap

MapToPair

SQL

StreamCorrection

TransformByKey

Deduplication

Data Cleansing

Filter

Imputation

Take

Data Blending

Join

Union

Intersection

Distinct

Group

Reconcile

Sort

Data Enrichment

Enricher

LookUps

Web-services

Expressions

SQL

Statistical and Temporal Analytics

Histogram

Standard Deviation

Average

Minimum Aggregation

Maximum Aggregation

Sum

Count

Associative Aggregation

Cumulative Aggregation

Square Root

Complex Event Processing

Window

Sliding window operations

Fixed Window operations

Alert & Reporting

Set thresholds on key metrics and corresponding action triggers, through real-time alerts

Alert

Streaming

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

SparkMLlib

Alternating Least Square

Ensemble

Isotonic Regression

k-Means

Logistic Regression

Naïve Bayes

Regression

Streaming K-means

Streaming Linear Regression

Support Vector Machine

Tree Model

Decision Tree

Apache Spark 2.1 Transformations

IDF

Word2Vec

Count Vectorized

Tokenizer

Stop Words Remover

N-gram

PCA

String Indexer

Index To String

One Hot Encoder

Vector Indexer

Normalizer

Min Max Scaler

Max Abs Scaler

Bucketizer

Vector Assembler

HashingTF

Stander Scalar

PMML

Regression

Logistic Regression Cluster Model Support Vector

Cluster Model

Support Vector

Association Rules

Neural Network

Naïve Byes

Tree Model

Ensemble

Online Learning

Streaming k-Means

Streaming Linear Regression

Streaming Logistic Regression

Extensibility

Keep full control and flexibility to add new functionality and interfaces as the technology ecosystem evolves

Custom Transformations and Functions

MVEL

Scala

Java

Python

Custom Processor

Custom Channel

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