Best IT Security Software for Apache Spark

LogIsland is the heart of Hurence’s real-time analytics. It allows you to capture factory events, IIoT, and events from your websites. Hurence says that a factory or, more broadly, a company can be understood and monitored in real-time through all events that it encounters. A sales order is an example of an event, while the production of a piece of robot-controlled machinery is an instance of an event, and the delivery of a product an event. Every event is an event. LogIsland allows you to capture all of these events, place them in a messagebus for large volumes, and analyze them in real-time with plug and play analyzers. These analyzers range from simple (counting alerts, recommendations), up to more complex artificial intelligence models for detection and prediction of anomalies and defects. You have two options for real-time analysis of events: custom analyzers for web analytics or industry 4.0.

Sematext Cloud provides all-in-one observability solutions for modern software-based businesses. It provides key insights into both front-end and back-end performance. Sematext includes infrastructure, synthetic monitoring, transaction tracking, log management, and real user & synthetic monitoring. Sematext provides full-stack visibility for businesses by quickly and easily exposing key performance issues through a single Cloud solution or On-Premise.

Our platform allows businesses to use data, including its application in advanced analysis, machine learning and AI, to do great things without worrying that customers, employees or intellectual property are at risk. The Protegrity Data Protection Platform does more than just protect data. It also classifies and discovers data, while protecting it. It is impossible to protect data you don't already know about. Our platform first categorizes data, allowing users the ability to classify the type of data that is most commonly in the public domain. Once those classifications are established, the platform uses machine learning algorithms to find that type of data. The platform uses classification and discovery to find the data that must be protected. The platform protects data behind many operational systems that are essential to business operations. It also provides privacy options such as tokenizing, encryption, and privacy methods.

We make BI and Big Data analytics easier and more efficient. Our goal is to empower business users, make BI specialists and always-busy business more independent when solving data-driven business problems. Querona is a solution for those who have ever been frustrated by a lack in data, slow or tedious report generation, or a long queue to their BI specialist. Querona has a built-in Big Data engine that can handle increasing data volumes. Repeatable queries can be stored and calculated in advance. Querona automatically suggests improvements to queries, making optimization easier. Querona empowers data scientists and business analysts by giving them self-service. They can quickly create and prototype data models, add data sources, optimize queries, and dig into raw data. It is possible to use less IT. Users can now access live data regardless of where it is stored. Querona can cache data if databases are too busy to query live.

Unlike most data management systems, PHEMI Health DataLab is built with Privacy-by-Design principles, not as an add-on. This means privacy and data governance are built-in from the ground up, providing you with distinct advantages: Lets analysts work with data without breaching privacy guidelines Includes a comprehensive, extensible library of de-identification algorithms to hide, mask, truncate, group, and anonymize data. Creates dataset-specific or system-wide pseudonyms enabling linking and sharing of data without risking data leakage. Collects audit logs concerning not only what changes were made to the PHEMI system, but also data access patterns. Automatically generates human and machine-readable de- identification reports to meet your enterprise governance risk and compliance guidelines. Rather than a policy per data access point, PHEMI gives you the advantage of one central policy for all access patterns, whether Spark, ODBC, REST, export, and more

Multi-cloud data security with a single pane of glass Industry's first SaaS access governance solution. Cloud is fragmented and data is scattered across different systems. Sensitive data is difficult to access and control due to limited visibility. Complex data onboarding hinders data scientist productivity. Data governance across services can be manual and fragmented. It can be time-consuming to securely move data to the cloud. Maximize visibility and assess the risk of sensitive data distributed across multiple cloud service providers. One system that enables you to manage multiple cloud services' data policies in a single place. Support RTBF, GDPR and other compliance requests across multiple cloud service providers. Securely move data to the cloud and enable Apache Ranger compliance policies. It is easier and quicker to transform sensitive data across multiple cloud databases and analytical platforms using one integrated system.

Complexity is the enemy of security. Simplify and scale fine-grained data access control. Dynamically authorize and audit every query to comply with data security and privacy regulations. Okera integrates seamlessly into your infrastructure – in the cloud, on premise, and with cloud-native and legacy tools. With Okera, data users can use data responsibly, while protecting them from inappropriately accessing data that is confidential, personally identifiable, or regulated. Okera’s robust audit capabilities and data usage intelligence deliver the real-time and historical information that data security, compliance, and data delivery teams need to respond quickly to incidents, optimize processes, and analyze the performance of enterprise data initiatives.

Alibaba Group has developed Log Service, a comprehensive real-time data log service. Log Service allows log collection, consumption, shipping, searching, and analysis. It also improves the processing and analysis of large log volumes. In five minutes, completes data collection from more than 30 sources. High-availability service nodes are deployed in data centers all over the world. Fully supports offline and real-time computing and seamlessly connects with open-source, commercial, and Alibaba Cloud software. You can adjust the access permissions to individual rows so that different reports are displayed for different user roles.

You have the freedom to choose the anonymization method that best suits your needs - including tokenization, encryption, and masking techniques. This will ensure that sensitive data is protected in a delicate balance between security and performance. You can choose from over 60 different anonymization methods to protect sensitive data. Anonymization methods that provide consistent results across datastores and applications will help you maintain referential integrity. Anonymization methods that provide both performance and protection. You can choose to encrypt, tokenize or mask data depending on the use case. There are many ways to anonymize sensitive data. Each method provides adequate security and data usability. Protect sensitive data across data storage and applications, and maintain referential integrity. You can choose from a range of NIST-approved encryption or tokenization algorithms.

iMask protects sensitive data at the Application Layer as well as the Database Layer. It offers flexible solutions that can be used for all types of use and all users, small, medium and large. Mask sensitive data at both the application and database levels to ensure your data's protection in production. You can set up rules in the product UI to allow role-based and user-based access controls that control who can access your sensitive information. You have the option to choose from more than 40 anonymization methods to maintain data consistency between production and nonproduction instances. You can set authorization rules to restrict who can see sensitive data based on geography, roles, departments, and other factors. Secure anonymization protocols can be enabled without affecting performance. Database embedded approach allows data to be deidentified without any changes in the application architecture or security protocols.

Real Identity™, delivers subsecond decisions to power relevant messages in a real-time environment. Real Identity allows the world's largest brands to ethically identify and connect with people anywhere, anytime to create relevant experiences. Engage people with precision, scale, and reach across all interactions You can manage and maintain your identity across your enterprise with 50 years of identity and data expertise, combined with the most recent artificial intelligence and machine-learning techniques. Adtech requires fast access to identity and data in order to enable personalization and decision making. These functions will be driven by first-party data signals in a cookieless environment. The conversation between publishers, brands, and people will continue to be between them. Delivering experiences that matter across all channels will allow you to wow your customers and prospects while also staying ahead of the regulations and your competitors.

Graph analytics can uncover hidden risks and uncover new opportunities. Standard MDM solutions do not support large volumes of disparate, distributed data that is generated by different applications and external sources. Traditional MDM probabilistic match doesn't work well when there are multiple data sources. It leaves out business value by missing connections and losing context. Ineffective MDM solutions can have a negative impact on everything, from customer experience to operational performance. Your team won't be able to make timely decisions without on-demand visibility into holistic payment patterns, trends, and risk. Compliance costs will rise, and coverage can't be increased quickly enough. Customers suffer from fragmented experiences due to the disconnect between your data and their business lines. Personalized engagement is not possible because they are based on incomplete, often outdated data.

Protect, Monitor, and Discover enterprise sensitive data across multiple platforms and environments. Automate your subject rights response and demonstrate regulatory compliance - all in one solution

Platform for enterprises that enables organizations to unlock sensitive information and run general-purpose AI workloads in the cloud on encrypted data, with verifiable security. Due to privacy concerns, organizations have huge amounts of confidential information locked down. Opaque Systems turns confidential data into useful information by enabling secure machine learning and analytics on encrypted data from multiple sources. Opaque Systems allows organizations to analyze encrypted data using popular tools such as Apache Spark in the cloud, while ensuring their data is never unencrypted by the cloud provider. Opaque Systems commercializes MC2 Platform, an open-source platform that combines two key technologies: secure hardware enclaves with cryptographic fortification. This combination ensures the overall computation to be secure, fast and scalable.