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What is Hackolade?

Hackolade Studio is a next-generation data modeling solution designed for today’s diverse and hybrid data environments. Initially created to fill the gap in visual modeling tools for NoSQL, Hackolade has expanded into a multi-model platform supporting a wide range of modern technologies. It enables agile schema design and governance for both structured and semi-structured data, making it well-suited for teams working across relational databases, NoSQL stores, data warehouses, and streaming systems. Supported technologies include Azure SQL, Oracle, PostgreSQL, SQL Server, MongoDB, Cassandra, DynamoDB, Neo4j, BigQuery, Databricks, Redshift, Snowflake, and Kafka with Confluent Schema Registry, as well as OpenAPI and GraphQL for API modeling. Hackolade also offers support for data exchanges stored on AWS S3, Azure Blob Storage and ADLS Gen1 and Gen 2, for formats such as JSON Schema, Avro, Parquet, Protobuf, and YAML. It also integrates with metadata governance tools like Unity Catalog and Collibra. These integrations help organizations maintain compliance, manage lineage, and ensure high data quality across systems. Key features include forward and reverse engineering, schema versioning, type mapping, and collaborative model design. Whether modeling new systems, documenting legacy databases, or managing API data contracts, Hackolade provides a centralized, visual interface that helps teams design and evolve schemas efficiently. Enterprises in finance, healthcare, telecom, and retail use Hackolade to support initiatives in data governance, data mesh, API-first development, and cloud migration, making it a key tool in the modern data stack.

What is Data Quality Validator (DQV)?

DQV is an all-encompassing platform for data quality and testing, designed by Kumaran Systems, specifically for teams managing, masking, or validating large datasets. This sophisticated tool systematically assesses both source and target datasets on a granular level, pinpointing inconsistencies and generating comprehensive mismatch reports, thereby removing the necessity for tedious manual verification through spreadsheets. It boasts five essential features: it conducts field-level comparisons while identifying drift, enables migration mapping across diverse schemas, provides deterministic PII masking, performs validation at both record and table levels with the capability for immediate corrections, and creates synthetic data for teams without access to production environments for testing purposes. DQV supports a variety of data sources, such as SQL Server, Oracle, MySQL, PostgreSQL, AWS, Azure, GCP, flat files, JSON, XML, and REST APIs, and it integrates effortlessly with tools like Informatica, Databricks, and CI/CD pipelines. Alternatively, it can function independently as a library or command-line interface tool. In practical scenarios, DQV has demonstrated impressive performance by successfully validating 26.6 million bank records in under 22 minutes, underscoring its remarkable efficiency. Furthermore, it offers a free trial along with diverse licensing choices, including individual, enterprise, and on-premises plans, catering to the varied needs of organizations. This adaptable solution not only improves data integrity but also simplifies the testing workflow across multiple platforms, making it an invaluable asset for data management teams.

Media

Media

No images available

Integrations Supported

Amazon DynamoDB
Apache Atlas
Apache CouchDB
Apache HBase
Apache Hive
Apache Kafka
Azure Repos
Elasticsearch
Firebase
GitLab
MarkLogic
MySQL
Oracle Database
OrientDB
PostgreSQL
Redis
Redshift
Swagger
SwaggerHub
TigerGraph

Integrations Supported

API Availability

Has API

API Availability

Pricing Information

€175 per month
Annual subscriptions possible
Volume discount possible
Possibility to purchase consurrent (floating) licenses via purchase order
Free Version
Free Trial Offered?

Pricing Information

Pricing not provided
Free Trial Offered?

Supported Platforms

SaaS
Windows
Mac
Linux

Supported Platforms

SaaS

Customer Service / Support

24 Hour Support
Web-Based Support

Customer Service / Support

Not specified

Training Options

Documentation Hub
Webinars
Online Training

Training Options

Not specified

Company Facts

Organization Name

Hackolade

Date Founded

2016

Company Location

Belgium

Company Website

hackolade.com

Company Facts

Organization Name

Kumaran Systems

Date Founded

1992

Company Location

United States

Company Website

kumaran.com/products/dqv/

Categories and Features

Data Modeling

Not specified

Database Design

Not specified

Metadata Management

Not specified

Categories and Features

Data Quality

Not specified

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