TIME MATTERS.
And still, up to 80% of time spent on stream processing goes NOT to value-adding operations or money-yielding apps, but on data wrangling.
SQLstream’s efforts to streamline data wrangling as an integral part of streaming analytics awarded us 5/5 scores for data connectors, transformation operators, and correlation operators in the prestigious The Forrester Wave™: Streaming Analytics, Q3 2017.
Continuous Discovery & Ingestion
SQLstream Blaze simplifies and accelerates data ingest for all formats. There is no need to hand-code data pipelines or re-create low-level code. The batch-oriented limitations of Big Data processing and traditional ETL are removed. All data formats including log files, web logs, sensor or IoT data, machine data, and CDC from databases, may be ingested, filtered, parsed, and simultaneously enriched with structured, stored data, from any or many sources for analysis.
Pre-analysis to rectify, fill, and make use of records affected by:
Streaming Data Integration
Machine data from log files, sensor networks, and applications contains a wealth of information most companies can’t use, because they can’t translate formats into a common language. But if you can’t see it, you can’t use it.
SQLstream Blaze integrates all data in real time, to help you make decisions based on customer and consumer behavior, location, QoS/QoE, financial transactions, security and compliance breaches, the state of your industrial processes, transportation networks, equipment health, and so on.
SQLstream Blaze’s log adapter turns any log file into a stream of real-time updates. Data from any log file type and format can be collected and analyzed. Complete log files or just updates can be collected, and log data joined, transformed and aggregated as needed.
Common examples include:
Many application servers including JBoss, Websphere and WebLogic generate log files using standard logging frameworks such as log4j. The data contains critical insights into application and application server operation and performance, but also the transaction information offers insights into business transactions and in particular fraud and security problems.
Call Detail Records (CDRs) and IP Data Records (IPDRs) are generated by telecoms network equipment for every call and session, and contain the information necessary to produce billing records. They also contain information that can be used to determine service quality and customer experience issues, particularly when joined in real-time with GPS and location data.
Clickstream data captures users’ activity on websites. It contains valuable information on visitor activity that can be used to alert on customer experience issues, drive real-time ad placement and detect shopping cart abandonments for example.
Deep Packet Inspection (DPI) tools use network probes to extract detailed information on connections, services and sessions. DPI probes generate a vast amount of real-time data that must be captured, correlated and combined into end-to-end connection and service information. The data contains key insights into Quality of Service, capacity management and network performance issues, as well as indicators of security attacks and breaches.
GPS data records the exact position of a device at a specific moment in time. GPS events can be transformed easily into position and movement information, for example for vehicles on a road network, or mobile subscribers with smartphones. Telecommunications, transportation, logistics and telematics rely on the accurate and sophisticated processing of GPS information.
All IP network equipment from the major vendors use syslog formation to capture connection status, capacity information, routing information, failure alerts, security alerts and performance data. When processed in real-time, and when data from all sources can be joined and queried simultaneously, this data provides a unique insight into the operation of the network and offers a platform for predictive analytics and forecasting.
The availability of low-cost, intelligent sensors, coupled with the latest 3G and 4G wireless technology has driven a dramatic increase in the volume of sensor data, but also the need to extract operational intelligence in real-time from the data. Examples include industrial automation plants, smart metering, environmental monitoring and the oil and natural gas industry.
Supervisory Control and Data Acquisition (SCADA) is the data management infrastructure for industrial control systems. SCADA systems produce an immense volume of measurement data, status information and failure alerts, and is widely deployed for remote equipment process monitoring across the smart grid, oil and natural gas, transportation and utilities sectors.
Data Enrichment
SQLstream Blaze can re-stream historical data and integrate it with the raw streams before running queries, for a complete and more accurate business context.
Better than Lambda
SQLstream Blaze is the only stream analytics platform that enriches raw data as it arrives with reference data from any or multiple databases in true real time. Unstructured, structured, local, distributed, in-motion and at-rest data may be integrated and analyzed continuously and at rates of millions of records per second per core. Our bidirectional read/write/update connections enable:
READY TO GIVE IT A TRY?
SQLstream Blaze is free to download and use up to 1GB/day (after which it throttles).
Guavus SQLstream’s mission is to make real-time stream analytics easy to use and own with a one-stop-shop solution that performs the best, has the widest footprint, never turns off, and can be developed and customized by data scientists and engineers alike.
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