• Relational RDBMS: SQL Server/Azure SQL,, DB2, MariaDB, MySQL, Oracle and Autonomous, PostgreSQL, YugabyteDB
• Big Data analytics: BigQuery, Databricks, Delta Lake, Hive and HDInsight, HBase, Redshift, Snowflake, Synapse, Teradata
• Document databases: MongoDB, Oracle JSON Collections, Amazon DocumentDB, Azure Cosmos DB - MongoDB vCore, Couchbase, Cosmos DB, Elasticsearch, MarkLogic
• Column-oriented: HBase, Cassandra, DataStax, ScyllaDB
• Key-value stores: DynamoDB
• Graph databases: Neo4j, JanusGraph, Amazon Neptune, TinkerPop/Gremlin
• Multi-model: ArangoDB, MarkLogic, Azure Cosmos DB for NoSQL API, MongoDB API, and Gremlin API
• APIs: Swagger/OpenAPI, GraphQL
• Storage formats: JSON Schema, Avro schema, Parquet, Protobuf, YAML
• Data catalogs: AWS Glue Data Catalog, Databricks Unity Catalog
• Schema registries: Confluent Schema Registry, Azure EventHubs, AWS EventBridge, Pulsar Schema Registry
• Cloud storage: AWS S3, Azure Blob Storage, Azure Data Lake Storage, Google Cloud Storage
• Git repository providers: GitHub, GitLab, Bitbucket, Azure DevOps Repos
• Metadata Management suites, data dictionaries, enterprise architecture: Collibra, Bizzdesign

With support for multiple database platforms and data exchanges, Hackolade Studio offers robust tooling for schema design plus forward- and reverse-engineering. Whether working with NoSQL databases, cloud platforms, or traditional RDBMS environments, Hackolade Studio helps users build and maintain scalable, well-documented models for transactional databases, data lakes, warehouses, APIs, and more. It also promotes collaborative data modeling, making it easier to manage cloud migrations and digital transformations, and keep teams aligned.

Key features of Hackolade Studio include:

• A flexible and intuitive interface for conceptual, logical, and physical data modeling.
• Capabilities for Entity-Relationship diagrams (ERD), graph, dimensional, JSON, and Data Vault modeling.
• Advanced data model comparison, synchronization, and change tracking.
• Creation of artifacts in a variety of formats (forward-engineering): DDLs, schemas, scripts.
• Automatic generation of visual models from existing databases with reverse-engineering.
  
• Native support for Git and Git providers: GitHub, Azure DevOps Repos, Bitbucket, and GitLab.
• Distributed model repository with tools for collaboration, versioning, branching, change tracking, conflict resolution, peer review processes.
  
• Powerful Command-Line Interface for easy integration with DevOps CI/CD pipelines.
• Detailed reporting and options for publishing models and metadata online.
• Wide-ranging support for different DBMS types, including major SQL, NoSQL and cloud databases.
  
• Integration with external enterprise architecture and data governance platforms.

Hackolade Studio provides the tools and features organizations need to ensure efficient, collaborative, and consistent management of their data environments.