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Control DControl D is a versatile DNS filtering and traffic redirection service that utilizes advanced Secure DNS protocols such as DNS-over-HTTPS, DNS-over-TLS, and DNS-over-QUIC, while also accommodating traditional DNS. With Control D, users can effectively eliminate harmful threats, restrict various types of undesirable content across the network—including advertisements, trackers, IoT data, adult material, social media, and more—while also redirecting traffic through transparent proxies and monitoring network activities and usage patterns at a client-specific level. Consider it your own personalized Authoritative DNS resolver for the entire Internet, providing you with detailed control over which domains are allowed to be resolved, redirected, or blocked. This capability not only enhances security but also empowers users to tailor their online experience according to their preferences.
What is SQLstream?
In the realm of IoT stream processing and analytics, SQLstream has been recognized as the leading solution by ABI Research. Our technology, utilized by major corporations such as Verizon, Walmart, Cisco, and Amazon, facilitates applications across various environments, including on-premises, cloud, and edge computing.
SQLstream's capabilities allow for the generation of urgent alerts, dynamic dashboards, and immediate responses with latency measured in sub-milliseconds. This enables smart cities to efficiently redirect emergency services and optimize traffic signal operations based on current conditions. Additionally, security frameworks can swiftly identify and neutralize cyber threats, ensuring safety and integrity. Furthermore, AI and machine learning models, developed using streaming sensor inputs, are capable of forecasting potential equipment malfunctions.
Due to SQLstream's remarkable speed — accommodating up to 13 million rows per second for each CPU core — organizations have significantly minimized their operational costs and physical infrastructure. Our advanced in-memory processing fosters capabilities at the edge that would typically be unfeasible.
Users can acquire, prepare, analyze, and take action on data across various formats and sources seamlessly. With StreamLab, our user-friendly, low-code development environment, creating data pipelines becomes a task that can be accomplished in minutes rather than months. Instant script editing and real-time result visualization without the need for compilation streamline the development process further. Deployment is made easier with robust support for Kubernetes, simplifying integration into existing workflows.
The installation process is user-friendly and compatible with a variety of platforms, including Docker, AWS, Azure, Linux, VMWare, and others, ensuring flexibility for diverse operational needs.
What is Apache Spark?
Apache Spark™ is a powerful analytics platform crafted for large-scale data processing endeavors. It excels in both batch and streaming tasks by employing an advanced Directed Acyclic Graph (DAG) scheduler, a highly effective query optimizer, and a streamlined physical execution engine. With more than 80 high-level operators at its disposal, Spark greatly facilitates the creation of parallel applications. Users can engage with the framework through a variety of shells, including Scala, Python, R, and SQL. Spark also boasts a rich ecosystem of libraries—such as SQL and DataFrames, MLlib for machine learning, GraphX for graph analysis, and Spark Streaming for processing real-time data—which can be effortlessly woven together in a single application. This platform's versatility allows it to operate across different environments, including Hadoop, Apache Mesos, Kubernetes, standalone systems, or cloud platforms. Additionally, it can interface with numerous data sources, granting access to information stored in HDFS, Alluxio, Apache Cassandra, Apache HBase, Apache Hive, and many other systems, thereby offering the flexibility to accommodate a wide range of data processing requirements. Such a comprehensive array of functionalities makes Spark a vital resource for both data engineers and analysts, who rely on it for efficient data management and analysis. The combination of its capabilities ensures that users can tackle complex data challenges with greater ease and speed.
Integrations Supported
Acxiom InfoBase
Apache Kudu
Apache Kylin
BentoML
Daft
Databricks
Deequ
Gable
Gemini Enterprise Agent Platform Notebooks
HStreamDB
Integrations Supported
Acxiom InfoBase
Apache Kudu
Apache Kylin
BentoML
Daft
Databricks
Deequ
Gable
Gemini Enterprise Agent Platform Notebooks
HStreamDB
API Availability
Has API
API Availability
Has API
Pricing Information
Pricing not provided.
Free Trial Offered?
Free Version
Pricing Information
Pricing not provided.
Free Trial Offered?
Free Version
Supported Platforms
SaaS
Android
iPhone
iPad
Windows
Mac
On-Prem
Chromebook
Linux
Supported Platforms
SaaS
Android
iPhone
iPad
Windows
Mac
On-Prem
Chromebook
Linux
Customer Service / Support
Standard Support
24 Hour Support
Web-Based Support
Customer Service / Support
Standard Support
24 Hour Support
Web-Based Support
Training Options
Documentation Hub
Webinars
Online Training
On-Site Training
Training Options
Documentation Hub
Webinars
Online Training
On-Site Training
Company Facts
Organization Name
Guavus, a Thales company
Date Founded
2006
Company Location
United States
Company Website
sqlstream.com
Company Facts
Organization Name
Apache Software Foundation
Date Founded
1999
Company Location
United States
Company Website
spark.apache.org
Categories and Features
Streaming Analytics
Data Enrichment
Data Wrangling / Data Prep
Multiple Data Source Support
Process Automation
Real-time Analysis / Reporting
Visualization Dashboards
Categories and Features
Big Data
Collaboration
Data Blends
Data Cleansing
Data Mining
Data Visualization
Data Warehousing
High Volume Processing
No-Code Sandbox
Predictive Analytics
Templates
Data Analysis
Data Discovery
Data Visualization
High Volume Processing
Predictive Analytics
Regression Analysis
Sentiment Analysis
Statistical Modeling
Text Analytics
Streaming Analytics
Data Enrichment
Data Wrangling / Data Prep
Multiple Data Source Support
Process Automation
Real-time Analysis / Reporting
Visualization Dashboards