NoSQL databases

Cassandra
Cosmos DB
Couchbase
DynamoDB
Elasticsearch
Firebase
Firestore
HBase
JSON REST APIs
MongoDB

Apache Cassandra and DataStax

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.

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

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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 DocumentDB and MongoDB APIs.

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Couchbase

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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Elasticsearch

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 Cloud Firestore

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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JSON RESTful APIs

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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MongoDB

Data modeling for GIANT ideas

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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