Spark Integrations

Business Intelligence, AI & NLP are available to anyone who wants to make data-driven business decisions. Knowi instantly transforms data into insights and data-driven actions. No ETL. No ODBC drivers. Simply connect your datasources to start building queries. It's that simple. In a matter of minutes, you can create blended datasets by joining data sources from NoSQL and SQL, REST API, and even file-based sources. Click. Done. We have combined the power and natural language queries of AI to create a new self-service experience in BI that makes it easier to find and reveal new insights. The data we have today is large and scattered. A business intelligence solution is required to instantly connect to modern data. Knowi is the only full-stack analytics platform that integrates natively to all popular NoSQL data sources, as well as relational or Cloud APIs.

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.

Datameer is your go-to data tool for exploring, preparing, visualizing, and cataloging Snowflake insights. From exploring raw datasets to driving business decisions – an all-in-one tool.

Algonomy is powered with a proven real time customer data and analytics platform, and global retail expertise. You can now precisely integrate demand and supply, engage customers with contextually pertinent experiences throughout their lifecycle, and enable rapid time to market, resulting in immediate ROI for your company. The new digital world is based on decision-making, not data. Customers who are smart expect personalized engagement and deeper, more relevant experiences. Brands must be able to make immediate decisions to address what appear to be two competing goals: short-term conversion revenue and long-term lifetime values. Algonomy makes it easy to make this a reality. You can have AI-based actionability as well as deep domain-specific analytics. Algonomy was created by Manthan, a cloud analytics leader and RichRelevance, an experience personalization icon. This new combination gives retailers an immediate boost in digital competence.

HugeGraph is a high-speed, highly-scalable graph database. HugeGraph's excellent OLTP capability allows for the storage and querying of billions of edges and vertices. Gremlin, a powerful graph traversal and query language, can handle complex graph queries in compliance with Apache TinkerPop 3. It supports Gremlin and is compliant to Apache TinkerPop 3. Schema Metadata Management includes VertexLabel EdgeLabel PropertyKey and IndexLabel. Multi-type Indexes that support complex combination queries, range query, and exact query. Plug-in Backend Store Driver Framework. Supports RocksDB, Cassandra and ScyllaDB. It is easy to add another backend store driver if necessary. Integration with Hadoop/Spark. HugeGraph is built on the TinkerPop framework. We refer to the storage structure and schema definition of DataStax.

BDB is a modern data analysis and BI platform that can dig deep into your data to uncover actionable insights. It can be deployed on-premise or in the cloud. Our unique microservices-based architecture includes elements such as Data Preparation and Predictive, Pipeline, Dashboard designer, and Pipeline. This allows us to offer customized solutions and scalable analysis to different industries. BDB's NLP-based search allows users to access the data power on desktop, tablet, and mobile. BDB is equipped with many data connectors that allow it to connect to a variety of data sources, apps, third-party API's, IoT and social media. It works in real-time. It allows you to connect to RDBMS and Big data, FTP/ SFTP Server flat files, web services, and FTP/ SFTP Server. You can manage unstructured, semi-structured, and structured data. Get started on your journey to advanced analysis today.

DashDB Local is the newest edition of the IBM dashDB family. It provides organizations with the most flexible architecture to lower the cost of analytics in the dynamic worlds of big data and cloud. How is this possible? Analytics workloads can be easily moved and optimized by a common engine with different deployment options across public and private clouds. DashDB Local is an option if you prefer to deploy on a hosted private clouds or on-premises private clouds through a software defined infrastructure. DashDB Local is easy to deploy and manage from an IT perspective. It uses container technology with elastic scaling and simple maintenance. DashDB Local is user-friendly. It provides the speed to cycle through data acquisition, apply the right analytics to meet a particular use case, and then operationalizes the insights.

The CData API Server makes it easy to create and deploy data-driven APIs. API Server allows users to create APIs that provide back-ends to internal applications, enable mobile development projects, expose data and deploy microservices of enterprise-class quality. The API Server is an application that comes with everything you need to create, manage, secure, and run APIs. It does not require any custom development. It allows you to create and distribute self-contained API endpoints on-premise and to the cloud. These endpoints can connect to any database or application and translate REST, JSON and OData API calls into your IT resources. API server includes API-critical features such as access-control, data security monitoring and management. It is a powerful tool that can modernize your back-end infrastructure. Download a 30-day free trial of CData API Server or learn more at: https://www.cdata.com/apiserver/

Atlas is a flexible and extensible set core foundational governance services that enable enterprises to efficiently and effectively meet their compliance requirements within Hadoop. It also allows integration with the entire enterprise data ecosystem. Apache Atlas offers open metadata management and governance capabilities that allow organizations to create a catalog of their data assets, classify, govern and provide collaboration capabilities around these assets for data scientists, analysts, and the data governance group. Pre-defined types to manage various Hadoop and non Hadoop metadata. Ability to create new types to manage metadata. Types can inherit from other types, and can have simple attributes, complex attributes, and object references. Type instances, also known as entities, are able to capture metadata object details and their relationships. REST APIs allow for easier integration with types and instances.

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.