Apache Cassandra and DataStax

cassandra datastax data modeling

Linear scalability and proven fault-tolerance on commodity hardware or cloud infrastructure

The Apache Cassandra database is the right choice when you need scalability and high availability without compromising performance, and with no single point failure.

Hackolade was specially adapted to support the data modeling of Cassandra, including User-Defined Types and the concepts of Partitioning and Clustering keys. It lets users define, document, and display Chebotko physical diagrams. The application closely follows the Cassandra terminology, data types, and Chebotko notation.

The reverse-engineering function includes the table definitions, indexes, user-defined types and functions, but also the inference of the schema for JSON structures if detected in text or blob

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Azure Cosmos DB

Data modeling of document collections

Azure Cosmos DB is Microsoft's globally distributed, multi-model database to elastically and independently scale throughput and storage across any number of Azure's geographic regions.

Hackolade was specially adapted to support the data modeling of multiple document types within one single collection. Each Document Type is modeled as a separate entity, so its attributes can be defined separately. We support both SQL API (formerly known as DocumentDB API) and MongoDB API.

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couchbase data modeling

Couchbase

couchbase data modeling

Data modeling of multiple object types within one single bucket, or multiple buckets, if preferred

Couchbase Server has become the de facto standard for building Systems of Engagement. It is designed with a distributed architecture for performance, scalability, and availability. It enables developers to build applications easier and faster by leveraging the power of SQL with the flexibility of JSON.

Hackolade was specially adapted to support the data modeling of multiple object types within one single bucket. Each Document Kind is modeled as a separate entity, so its attributes can be defined separately.

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AWS DynamoDB

Data modeling of fully managed cloud NoSQL database service

Amazon DynamoDB is a fast and flexible NoSQL database service for all applications that need consistent, single-digit millisecond latency at any scale. It is a fully managed cloud database and supports both document and key-value store models. Its flexible data model and reliable performance make it a great fit for mobile, web, gaming, ad tech, IoT, and many other applications.

Hackolade was specially adapted to support the data modeling of DynamoDB tables including partition (hash) and sort (range) keys, supporting multiple regions as well.

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dynamodb data modeling

Elasticsearch

elasticsearch data modeling

When you get answers instantly, your relationship with your data changes.

Elasticsearch is a RESTful search and analytics engine based on Apache Lucene. It provides a distributed, multitenant-capable full-text search engine with an HTTP web interface and schema-free JSON documents.

Hackolade was specially adapted to support the data modeling of Elasticsearch, including the large choice of data types, and parent-child relationships. We dynamically generate mappings for forward-engineering, and infer schema through document sampling and mappings if available.

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Google RealTime Firebase

Mobile app success made simple

The Google Firebase Realtime Database is a cloud-hosted database. Data is stored in JSON and synchronized in real time to every connected mobile or other client. It lets developers build rich collaborative applications, with data also persisted locally, to give users a responsive experience.

Hackolade was specially adapted to support the data modeling of data stored as a large JSON tree, with data nodes and their associated keys.

Note: the forward- and reverse-engineering of schemas are not currently available. They're being developed and will be released at a later time.

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Google RealTIme firebase data modeling

Google Cloud Firestore

Google Cloud Firestore data modeling

Store & sync data globally

Cloud Firestore is a flexible, scalable database for mobile, web, and server development from Firebase and Google Cloud Platform.

Hackolade was specially adapted to support the data modeling of data stored in collections, nested objects, and subcollections.

Note: the forward- and reverse-engineering of schemas are not currently available. They're being developed and will be released at a later time.

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Apache HBase

When you need random, realtime read/write access to your Big Data

Apache HBase is an open-source, distributed, versioned, non-relational database modeled after Google's Bigtable. This project's goal is the hosting of very large tables -- billions of rows X millions of columns -- atop clusters of commodity hardware.

Hackolade was specially adapted to support the data modeling of HBase, whether you store your data in column families or as a JSON object. With our reverse-engineering function, you can easily discover, document, and enrich the structure of your column families and qualifiers, plus infer the structure of JSON documents you store in HBase.

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hbase data modeling

JSON RESTful APIs

Plain JSON REST APIs data modeling

Ideal to perform the upfront design and documentation of REST APIs.

REST, short for REpresentational State Transfer, is a lightweight architectural style used when designing networked applications. Web service APIs that conform to the REST architectural constraints are known as RESTful, or REST API.

Hackolade was specially adapted to support the modeling of the underlying communication model of REST API, as well as the generation of REST APIs and API documents.

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MarkLogic

ACID multi-model NoSQL DB for the enterprise

MarkLogic is designed from the ground up to make massive quantities of heterogeneous data easily accessible through search. MarkLogic is a leading 'multi-model' database, supporting traditional relational tables, XML and JSON documents, and RDF triples, all with ACID transactions capabilities.

Hackolade was specially adapted to support the data modeling of MarkLogic, including the JSON definition of model descriptors, geospatial structures, triples and quads, and sub-collections. The application closely follows the terminology of the database.

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marklogic data modeling

MongoDB

mongodb mongodb data modeling

Data modeling for MongoDB

MongoDB can help you make a difference to the business. Tens of thousands of organizations, from startups to the largest companies and government agencies, choose MongoDB because it lets them build applications that weren’t possible before. With MongoDB, these organizations move faster than they could with relational databases at one tenth of the cost.

Hackolade was specially built to support the data modeling of MongoDB collections, pioneering a new set of software tools to smooth the onboarding of NoSQL technology in corporate IT landscapes, reduce development time, increase application quality, and lower execution risks.

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Neo4j

Data modeling for graph databases

Neo4j is a graph database management system described as an ACID-compliant transactional database with native graph storage and processing.
Hackolade was specially built to support the data modeling of Neo4j node labels and relationship types. It provides a graph view with familiar circular node labels, as well as an Entity-Relationship Diagram view with permanent display of the attributes (or properties) of both node labels and relationship types.
Hackolade dynamically generates Cypher code as the model is created via the application. It also lets you perform reverse-engineering of existing instances, so you can enrich the model with descriptions and constraints, then produce a complete, clickable HTML documentation for distribution to all application stakeholders.
The application closely follows the terminology of the database, pioneering a new set of software tools to smooth the onboarding of NoSQL technology in corporate IT landscapes, reduce development time, increase application quality, and lower execution risks.
Hackolade is not a graph visualization tool, but a tool for schema design of Neo4j graph databases.

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Neo4j graph data modeling Neo4j data modeling