Integrating SQLstream Blaze with Other Systems

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Integrating SQLstream Blaze with Other Systems

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Purpose

The purpose of this document is to describe the many different ways in which SQLstream s-Server can be integrated with external systems. Topics covered include:

Reading and writing data to RDBMS systems. These include Microsoft SQL Server, Oracle, MySQL, PostgreSQL, and Teradata.

The SQLstream JDBC driver. This driver lets applications connect to s-Server over JDBC. You can use the JDBC driver to implement federation for s-Server instances in a cluster of compute nodes.

Reading from Other Sources. You can read data from a variety of sources, including the file system, sockets, AMQP, Kafka, IBM MQ, Amazon Kinesis, HTTP, WebSockets, and web feeds. You can read from both local and remote sources. You can read from a variety of formats, including CSV, XML, JSON, Avro, Key Pair Values, ProtoBuf, Variable Column Data, Fixed Column Data, and W3C Data. You can also parse files with a FastRegex row filter. If you need information about the file to be parsed, including help on parsing options, you can use the Discovery Parser to get this information.

Writing to Other Destinations. You can write data to a variety of sources, including the file system, sockets, AMQP, Kafka, Amazon Kinesis, IBM MQ, HTTP, WebSockets, Snowflake warehouses, MongoDB categories, and mail servers. You can write to both local and remote sources. You can write files in CSV, XML,JSON, and BSON.

Transforming Data in s-Server, which describes built-in user-defined transformations and user-defined functions, such as the Linear Interpolation UDX and Quadratic Interpolation UDX (both of which allow you to interpolate missing rows), the Kalman Filter UDX, the Parser UDX (which lets you invoke the parsers described in Reading from other Sources above), Group Rank UDX and GeoIPFunctions UDX. s-Server now incorporates machine learning systems such as SystemML and DataRobot. See Using s-Server for Machine Learning with Integrated Apache SystemML and Building a UDX with DataRobot. You can now use run Kalman filters on streams of sensor data. A Kalman filter is a technique for sharpening the measurements produced by blurry sensors. See Using the Kalman Filter UDX.

SQLstream Software Development Kit (SDK), which includes information on how to write an Extensible Common Data Framework Plugin, how to write a User Defined Function (UDF) and how to write a User Defined Transform (UDX).

Audience

This document is aimed at developers and system architects.

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