This guide describes the many different ways in which SQLstream s-Server can be integrated with external systems. Topics covered include:
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, MQTT, Kafka, Amazon Kinesis, HTTP, and WebSockets. You can read from both local and remote sources. You can read from a variety of formats, including CSV, XML, JSON, Avro, Key Value Pairs, and ProtoBuf. 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, MQTT, Kafka, Amazon Kinesis, HTTP, WebSockets, Snowflake warehouses, MongoDB categories, Hadoop/HDFS and mail servers. You can write to both local and remote sources. You can write files in CSV, XML,JSON, BSON, and Avro .
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 DataRobot. See 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.