Complete Stream Processing

Visually manage your streaming data- from Source to Sink.


Streaming Ingestion

Guavus SQLstream acquires data from multiple, disparate sources with automated discovery features so you can easily to connect to data streams and start interacting with them with no coding necessary.

Streaming sources include:

  • Apache Kafka
  • AWS Kinesis
  • Http
  • Web sockets
  • Network Sockets
  • Files
  • Teradata Listener


Data Discovery

Guavus SQLstream saves you time and effort by automatically discovering the format of your streaming data, including column name, path and type. Edit names and types directly within StreamLab.

Discoverable Formats include:

  • Line
  • CSV
  • JSON
  • XML
  • Binary (Avro/ProtoBuf)


A data scientist can easily spend 50 to 80% of his time cleaning and preparing his data before he even starts looking for insights in it. StreamLab makes it easy to transform data into a format that makes it easier to work with.


  • Perform pre-analysis to rectify, fill, and make use of records affected by lack of data, delayed data, out-of-order data, erroneous data, etc.…
  • Interactive suggestions within StreamLab help you to build streaming SQL queries (sums, averages, statistical functions, etc.)
  • Preview live data as it flows through so that you can see filters and transformations continuously throughout the pipeline building process


Guavus SQLstream enables you to enrich event streams with data from external tables and other event streams so that all information is available and formatted for analysis.


  • Stream-table joins from MySQL, Oracle, PostgreSQL, SQL Server, Teradata, Actian, MongoDB, DB2, & Snowflake
  • Stream-stream joins 




Guavus SQLstream puts powerful analytics at your fingertips with features like Aggregate, Bollinger Bands, Calculate, Categorize, Group Rank, Table Lookup, Time Sort and New Column.

Detect trends to identify:

  • Threat Detection
  • Recommendations
  • Anomaly Detection
  • Predictive Analytics
  • Sentiment Analysis

Machine Learning

Guavus SQLstream provides an enterprise platform for hosting machine learning models for predictive analysis. By continuously filtering and transforming data, SQLstream ensures that data is ready for scoring. SQLstream’s advanced features allow users to programmatically define triggers and actions based on real-time machine learning scores.

  • Continuously train models
  • Incorporate updated models on-the-fly
  • Apache SystemML embedded
  • DataRobot & Anodot integrated




Automated Actions

Guavus SQLstream enables you to automate responses when certain criteria is met in real-time.

  • Freeze a bank account when fraud score is > .9
  • Change a traffic light when there are more than 4 cars queued up in the turn lane
  • Alert network security when an intrusion is detected
  • Send a coupon to a customer when a customer adds a related product to their shopping cart


Data Visualization

Guavus SQLstream can use native s-Dashboard visualization to push real-time updates to the browser or use our native web agent to push to external visualization tools.

Choose from dozens of dashboard templates:

  • Bar & Line Graphs
  • Geographical & 3-D Streams
  • Bollinger Bands
  • Time Series

Output Stream & Sinks

Once you have analyzed, enriched, or otherwise modified data, you will often want to write this data out of s-Server into other locations, or “sinks”.

Export data out to:

  • Kafka, Kinesis or AMQP Streams
  • Databases (SQL, NoSQL)
  • Datawarehouses
  • Web Services
  • Files
  • New or Existing Blaze Streams

Learn more


SQLstream Blaze is free to download and use up to 1GB/day (after which it throttles).