Data Integration Tools

K2view takes a data product approach to data integration.
Data engineers create and manage reusable data pipelines that integrate, process, and deliver data by business entities – customers, employees, orders, loans, etc.

The data for each business entity is ingested and organized into its own high-performance M icro-Database™.
The schema for a business entity is auto-discovered from the underlying source systems.
Data masking, transformation, enrichment, and orchestration are applied – in flight – to make entity data accessible to authorized data consumers, while complying with data privacy and security regulations.

K2view data integration includes no-code tooling for defining, testing, and debugging data transformations to address simple and complex needs, with ease. Data transformation is applied in the context of a business entity, making performance lightning fast, in support of high-scale data preparation and delivery.

Basic data transformations
Data type conversions, string manipulations, and numerical calculations.
Intermediate data transformations
Lookup/replace using reference files, aggregations, summarizations, and matching.
Advanced data transformations
Complex parsing, unstructured data processing, combining data and content sources, text mining, correlations, custom enrichment functions, data validation, and cleansing.

K2view Data Product Platform scales linearly to manage hundreds of concurrent pipelines, and billions of Micro-Databases, in support for high-scale operational and analytical data integration workloads.

In-memory computing, patented Micro-Database technology, and a distributed architecture, are integrated to deliver unmatched source-to-target data performance.
K2view can be deployed on premises or in the cloud, in support of a data mesh architecture, data fabric architecture, or data hub architecture.
Data pipelining monitoring and control is built in, with observability provided at the business entity level.

No-code/ low-code

No-code and low-code tooling to support varying levels of data engineering expertise

Any data sources

Connectors to hundreds data sources and applications

Any delivery method

Multiple data delivery styles, including CDC, ETL, streaming, and messaging

Data virtualization

Data virtualization support provides an easy-to-access logical abstraction layer

Data transformation

Data transformation of unprecedented sophistication

Auto-discovery

Metadata discovery and data classification accelerate implementation

Any data architecture

Deploy in a data mesh architecture, data fabric architecture, or data hub

Data quality

Data quality is enforced in-flight, through customizable business rules

Deploy anywhere

Support for cloud, hybrid, or on-premise data integration

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Enterprise Data Integration Tools

Integrate data from any data source, and make it accessible to any data consumer, in any method: bulk ETL, streaming, data virtualization, messaging, CDC, SQL, and APIs.

All data integration and delivery methods

From any source, to any target

Robust, reusable data integration

Entity-based data integration tools

A data product approach

Ingest and deliver data by business entities

easy and lightning-fast

No-code data integration and transformation

Linear scalability on commodity hardware

Real-time performance at enterprise scale

Key features and capabilities