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MindCloudMindCloud serves as a contemporary iPaaS and offers a comprehensive service solution tailored for small to medium-sized enterprises, allowing you to manage projects without the need for dedicated technical personnel. With an extensive library of over 50 pre-built connectors, we can also incorporate any new software platform equipped with an API or supports automated data imports and exports. In addition, we facilitate EDI and FTP integrations to enhance connectivity. Notable connectors include Salesforce, Monday.com, Hubspot, QuickBooks Desktop, QuickBooks Online, Method:CRM, Zapier, Walmart, Amazon, Overstock, eBay, Groupon, Mercado Libre, HSN, Airtable, Google Sheets, and a wide array of others. MindCloud empowers you to automate all your business processes effectively, thereby eradicating the need for redundant data entry. By integrating your business operations, you can streamline your workflow and improve your overall productivity, making your life easier in the process.
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CredentialStreamCredentialStream® utilizes innovative patented technology to facilitate the requesting, collection, and verification of provider information, ultimately creating a trustworthy Source of Truth for subsequent processes. Its cutting-edge platform is regularly enhanced and is supported by extensive content libraries and top-tier data sets, making CredentialStream the premier solution for managing the entire lifecycle of providers. Additionally, the seamless integration of these resources ensures that organizations can maintain compliance and efficiency in their operations.
What is Apache Kafka?
Apache Kafka® is a powerful, open-source solution tailored for distributed streaming applications. It supports the expansion of production clusters to include up to a thousand brokers, enabling the management of trillions of messages each day and overseeing petabytes of data spread over hundreds of thousands of partitions. The architecture offers the capability to effortlessly scale storage and processing resources according to demand. Clusters can be extended across multiple availability zones or interconnected across various geographical locations, ensuring resilience and flexibility. Users can manipulate streams of events through diverse operations such as joins, aggregations, filters, and transformations, all while benefiting from event-time and exactly-once processing assurances. Kafka also includes a Connect interface that facilitates seamless integration with a wide array of event sources and sinks, including but not limited to Postgres, JMS, Elasticsearch, and AWS S3. Furthermore, it allows for the reading, writing, and processing of event streams using numerous programming languages, catering to a broad spectrum of development requirements. This adaptability, combined with its scalability, solidifies Kafka's position as a premier choice for organizations aiming to leverage real-time data streams efficiently. With its extensive ecosystem and community support, Kafka continues to evolve, addressing the needs of modern data-driven enterprises.
What is Apache Druid?
Apache Druid stands out as a robust open-source distributed data storage system that harmonizes elements from data warehousing, timeseries databases, and search technologies to facilitate superior performance in real-time analytics across diverse applications. The system's ingenious design incorporates critical attributes from these three domains, which is prominently reflected in its ingestion processes, storage methodologies, query execution, and overall architectural framework. By isolating and compressing individual columns, Druid adeptly retrieves only the data necessary for specific queries, which significantly enhances the speed of scanning, sorting, and grouping tasks. Moreover, the implementation of inverted indexes for string data considerably boosts the efficiency of search and filter operations. With readily available connectors for platforms such as Apache Kafka, HDFS, and AWS S3, Druid integrates effortlessly into existing data management workflows. Its intelligent partitioning approach markedly improves the speed of time-based queries when juxtaposed with traditional databases, yielding exceptional performance outcomes. Users benefit from the flexibility to easily scale their systems by adding or removing servers, as Druid autonomously manages the process of data rebalancing. In addition, its fault-tolerant architecture guarantees that the system can proficiently handle server failures, thus preserving operational stability. This resilience and adaptability make Druid a highly appealing option for organizations in search of dependable and efficient analytics solutions, ultimately driving better decision-making and insights.
Integrations Supported
Acryl Data
Azure Marketplace
DataHub
Deep.BI
Emgage
Gravity Data
OpenMetadata
Stackable
Amundsen
AnzoGraph DB
Integrations Supported
Acryl Data
Azure Marketplace
DataHub
Deep.BI
Emgage
Gravity Data
OpenMetadata
Stackable
Amundsen
AnzoGraph DB
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
The Apache Software Foundation
Date Founded
1999
Company Location
United States
Company Website
kafka.apache.org
Company Facts
Organization Name
Druid
Date Founded
2013
Company Website
druid.apache.org/technology
Categories and Features
iPaaS
AI / Machine Learning
Cloud Data Integration
Dashboard
Data Quality Control
Data Security
Drag & Drop
Embedded iPaaS
Integration Management
Pre-Built Connectors
White Label
Workflow Management
Message Queue
Asynchronous Communications Protocol
Data Error Reduction
Message Encryption
On-Premise Installation
Roles / Permissions
Storage / Retrieval / Deletion
System Decoupling
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 Warehouse
Ad hoc Query
Analytics
Data Integration
Data Migration
Data Quality Control
ETL - Extract / Transfer / Load
In-Memory Processing
Match & Merge
Relational Database
ACID Compliance
Data Failure Recovery
Multi-Platform
Referential Integrity
SQL DDL Support
SQL DML Support
System Catalog
Unicode Support
