Explore streams through drag-and-drop

Through the StreamLab interface, you can easily discover and direct data to s-Server for processing. Data can be streamed from a log file, a Kafka topic, Kinesis, a network socket, an AMQP message, etc.

A range of different sources can be added, including:

• An External Stream Source
• An External Table Source
• A Blaze Stream Source
• A Public Data Source

Build, save, and update queries concurrently, continuously, and in real time

StreamLab can be used to run concurrent operations (such as integration, filtering, parsing, enriching, transformation, windowing, correlation, time-based and geospatial queries), through:

• Commands: sets of operations that you can perform on the guide’s data source. These include, for example, commands to parse the source as a W3C log, to parse a timestamp, to split a column at a given character, to remove a column, and to rename a column. Commands are grouped by functionality, and you can switch between command sets by clicking the Select Command Set button in the top left hand corner of the Guide.
• Suggestions: they appear in the Suggestions list in the middle left of the Guide interface, and change depending on your data source and your selection in the Output view. 
• Scripts: as you add suggestions to the script, these suggestions are implemented as SQL, with changes visible in the Output view. You can remove items from the script by clicking the – button. You can also visualize changes by clicking the View Dashboard button.

Build dashboards, monitor, and report in real time

Processed data is visualized in real time through StreamLab dashboards that can be built or updated ad-hoc while the system is running. Generating dashboards is easy and flexible, and can be done using Scripts, the Basic Dashboard command, or the Custom Dashboard command. 

Custom dashboards can include the following:

• Bar Graph
• Bouncing Bar Graph
• Bars and Lines
• Map and Table Dashboard
• Parallel Coordinates
• Bollinger Bands
• Scatter Matrix
• Time Series

Modifying dashboards is easy, with options to:

• Switch between Types of Layouts
• Enclose a Frame within a Layout
• Swap Panels
• Clone a Layout Frame

Real-time, continuous egress

StreamLab can be used to direct results to data stores for further use, and/or push data into live third-party executions (consumer applications, control systems, etc.), through the following types of external sinks:

• An External Stream sink that streams rows in comma-separated value, BSON, JSON, or XML form to a File System, MongoDB, Socket, AMQP, Kafka, or AWS Kinesis destination.
• An External Table sink that streams rows into a table in an external database. 

Intelligent formatting rules are applied automatically for common data source formats. Rulesets ensure that the data is structured correctly and common fields such as timestamps, IP addresses and geospatial coordinates identified correctly.

StreamLab’s graphical data stream browser allows analysts to view incoming data streams in real time and to enhance them via transformation rules. For example, an analyst can apply formatting and field identification rules, and save the output as a new Blaze stream. The Suggestions Tool identifies likely formatting and structuring issues and offers advice on how to correct any problems.

Real-time dashboards based on SQLstream s-Dashboard provide push-based, continuous visualization of real-time alerts and analytics. Dashboards include line graphs, bar charts, maps and text reports.